2020 |
Khowaja, K; Banire, B; Al-Thani, D; Sqalli, M T; Aqle, A; Shah, A; Salim, S S Augmented reality for learning of children and adolescents with autism spectrum disorder (ASD): A systematic review Journal Article IEEE Access, 8 , pp. 78779-78807, 2020, ISSN: 21693536, (cited By 0). Abstract | Links | BibTeX | Tags: Adolescent, Augmented Reality, Autism Spectrum Disorders, Bibliographic Database, Children, Classroom Environment, Data Acquisition, Data Collection, Diseases, Evaluation Parameters, Information Services, Maintenance, Parameter Estimation, Research, Social Communications @article #main 8, author = #main 7, url = #main 6, doi = #main 5, issn = #main 4, year = #main 3, date = #main 2, journal = #main 1, volume = #main 0, pages = [if lt IE 9]> publisher = [if lt IE 9]> abstract = [if lt IE 9]> note = [if lt IE 9]> keywords = [if lt IE 9]> pubstate = [if lt IE 9]> tppubtype = [if lt IE 9]> } This paper presents a systematic review of relevant primary studies on the use of augmented reality (AR) to improve various skills of children and adolescents diagnosed with autism spectrum disorder (ASD) from years 2005 to 2018 inclusive in eight bibliographic databases. This systematic review attempts to address eleven specific research questions related to the learing skills, participants, AR technology, research design, data collection methods, settings, evaluation parameters, intervention outcomes, generalization, and maintenance. The social communication skill was the highly targeted skill, and individuals with ASD were part of all the studies. Computer, smartphone, and smartglass are more frequently used technologies. The commonly used research design was pre-test and post-test. Almost all the studies used observation as a data collection method, and classroom environment or controlled research environment were used as a setting of evaluation. Most of the evaluation parameters were human-assisted. The results of the studies show that AR benefited children with ASD in learning skills. The generalization test was conducted in one study only, but the results were not reported. The results of maintenance tests conducted in five studies during a short-term period following the withdrawal of intervention were positive. Although the effect of using AR towards the learning of individuals was positive, given the wide variety of skills targeted in the studies, and the heterogeneity of the participants, a summative conclusion regarding the effectiveness of AR for teaching or learning of skills related to ASD based on the existing literature is not possible. The review also proposes the research taxonomy for ASD. Future research addressing the effectiveness of AR among more participants, different technologies supporting AR for the intervention, generalization, and maintenance of learning skills, and the evaluation in the inslusive classroom environment and other settings is warranted. © 2013 IEEE. |
Liang, S; Loo, C K; Sabri, Md A Q Autism Spectrum Disorder Classification in Videos: A Hybrid of Temporal Coherency Deep Networks and Self-organizing Dual Memory Approach Journal Article Lecture Notes in Electrical Engineering, 621 , pp. 421-430, 2020, ISSN: 18761100, (cited By 0). Abstract | Links | BibTeX | Tags: Artificial Intelligence, Autism Spectrum Disorders, Autistic Children, Catastrophic Forgetting, Children with Autism, Diagnosis, Diseases, E-learning, Hybrid Approach, Learning, Neural Networks, Primary Objective, Scalable Systems, Temporal Coherency, Unsupervised Online Learning @article[if lt IE 9]>
author = [if lt IE 9]>
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url = fusion-columns 9, doi = fusion-columns 8, issn = fusion-columns 7, year = fusion-columns 6, date = fusion-columns 5, journal = fusion-columns 4, volume = fusion-columns 3, pages = fusion-columns 2, publisher = fusion-columns 1, abstract = fusion-columns 0, note = fusion-row 9, keywords = fusion-row 8, pubstate = fusion-row 7, tppubtype = fusion-row 6 } Autism is at the moment, a common disorder. Prevalence of Autism Spectrum Disorder (ASD) is reported to be 1 in every 88 individuals. Early diagnosis of ASD has a significant impact to the livelihood of autistic children and their parents, or their caregivers. In this paper, we have developed an unsupervised online learning model for ASD classification. The proposed approach is a hybrid approach, consisting, the temporal coherency deep networks approach, and, the self-organizing dual memory approach. The primary objective of the research is, to have a scalable system that can achieve online learning, and, is able to avoid the catastrophic forgetting phenomena in neural networks. We have evaluated our approach using an ASD specific dataset, and obtained promising results that are well inclined in supporting the overall objective of the research. © Springer Nature Singapore Pte Ltd 2020. |
2019 |
Ismail, W; Zamin, N; Hanafi, M H; Mohamad, A H Institute of Electrical and Electronics Engineers Inc., 2019, ISBN: 9781728108513, (cited By 0). Abstract | Links | BibTeX | Tags: Architecture, Clouds, Computer-Based System, Diseases, Distributed Computer Systems, Health Care System, Hospitals, Non-Communicable Disease, Patient Rehabilitation, Rehabilitation Services, Scientific Studies, Stroke Patients, Telerehabilitation, Traditional Systems, Virtual Reality @conference fusion-row 5, author = fusion-row 4, url = fusion-row 3, doi = fusion-row 2, isbn = fusion-row 1, year = fusion-row 0, date = fusion-footer-widget-area 9, journal = fusion-footer-widget-area 8, pages = fusion-footer-widget-area 7, publisher = fusion-footer-widget-area 6, abstract = fusion-footer-widget-area 5, note = fusion-footer-widget-area 4, keywords = fusion-footer-widget-area 3, pubstate = fusion-footer-widget-area 2, tppubtype = fusion-footer-widget-area 1 } Rehabilitation in healthcare systems provides therapy and training to restore quality life after certain illness, addiction or accident. Currently, there is a significant unmet need for rehabilitation services, and it is frequently undervalued in the health system. As populations age and the prevalence of noncommunicable diseases and injuries increases, and the demand for rehabilitation grows, strengthening rehabilitation in health systems becomes ever more paramount. Conventional rehabilitation service can be costly and time consuming to people not living near the rehabilitation centres. Often people with lower income who live in rural areas refuse rehabilitation services due to the logistic issue. On the other hand, in urban areas, most people are too busy with their daily activities and unable to keep their therapy schedule consistently. In consequence, patients do not enjoy the actual benefit of rehabilitation because of a certain limitation such as cost and time. These limitations can be surpassed by putting telerehabilitation, an emerging area of performing rehabilitation medical treatment with the use of technology from a distance into practice. Scientific studies of telerehabilitation in the current literature are discussing primarily in the area of readiness, technologies, and illnesses such as children autism and heart failure. However, there is limited evidence about telerehabilitation service for stroke patients, concentrating on the pre-implementation and implementation stages, which makes this paper viable and significant, potentially for telerehabilitation implementation in Malaysia. This paper proposes a new conceptual model of hybrid telerehabilitation that combines several technological principles, such as cloud, virtual reality, and computer-based system. The model was derived based on a study of a public tertiary hospital in Malaysia. The current traditional system was investigated and discussed. A new telerehabilitation model is proposed to widen the access for rehabilitation to patients of all ages. © 2019 IEEE. |
Mubin, S A; Poh, Wee Ann M A Review on Gamification Design Framework: How They Incorporated for Autism Children Conference Institute of Electrical and Electronics Engineers Inc., 2019, ISBN: 9781728126104, (cited By 0). Abstract | Links | BibTeX | Tags: Design Frameworks, Diseases, Games, Gamification, Interaction Skills, Research @conference fusion-footer-widget-area 0, author = fusion-fusion-copyright-content 9, url = fusion-fusion-copyright-content 8, doi = fusion-fusion-copyright-content 7, isbn = fusion-fusion-copyright-content 6, year = fusion-fusion-copyright-content 5, date = fusion-fusion-copyright-content 4, journal = fusion-fusion-copyright-content 3, publisher = fusion-fusion-copyright-content 2, abstract = fusion-fusion-copyright-content 1, note = fusion-fusion-copyright-content 0, keywords = fusion-row 9, pubstate = fusion-row 8, tppubtype = fusion-row 7 } This paper presents a review of the literature on gamification design frameworks. Gamification is a term that has been used recently to depict games application in other non-game field. However, there is no specific gamification framework designed for autism children in supporting their interaction skills. Before gamification process begin, it is very important to identify which frameworks or model exist and their main elements related to the scopes. Poor gamification design leads to the challenge to fulfill the research objectives, which aimed to enhance autism interaction skills among children. This review classifies existing methods and offers valuable insight on gamified solutions for autism children in supporting their interaction skills. © 2019 IEEE. |
Aziz, N S A; Ahmad, W F W; Hashim, A S A study on mobile applications developed for children with autism Journal Article Advances in Intelligent Systems and Computing, 843 , pp. 772-780, 2019, ISSN: 21945357, (cited By 0). Abstract | Links | BibTeX | Tags: Autism, Children with Autism, Communication Skills, Diseases, Education, Educational Applications, Mobile Applications, Mobile Computing, Mobile Learning, Mobile Technology, Neurological Disorders, Soft Computing @article fusion-row 6, author = fusion-row 5, editor = fusion-row 4, url = fusion-row 3, doi = fusion-row 2, issn = fusion-row 1, year = fusion-row 0, date = #footer 9, journal = #footer 8, volume = #footer 7, pages = #footer 6, publisher = #footer 5, abstract = #footer 4, note = #footer 3, keywords = #footer 2, pubstate = #footer 1, tppubtype = #footer 0 } The emerging of mobile technology leads to the extensive used of mobile application for learning purposes of the children with autism. Autism is a neurological disorder that affects the children’s behavior and their ability to communicate and interact socially. A lot of studies have been conducted on using mobile application to assist the children with autism to increase their social and communication skills. Mobile applications are now widely used, not only for entertainment and social networking, but also for education. The used of mobile applications in education has extend from dictionaries to special purpose education. This paper reviews six mobile applications developed to assist the children with autism for various purposes. This review will provide a summary of initial studies and preliminary findings for future development of enhanced application. © Springer Nature Switzerland AG 2019. |
Khowaja, K; Salim, S S; Asemi, A; Ghulamani, S; Shah, A Universal Access in the Information Society, 2019, ISSN: 16155289, (cited By 2). Abstract | Links | BibTeX | Tags: Augmented Reality, Autism Spectrum Disorders, Children with Autism, Computer Aided Instruction, Decoding, Diseases, Language Comprehensions, Maintenance, Mammals, Multi-Modal Interfaces, Post Interventions, Reading Comprehension, Serious Games, Spectrum Analysis, Transfer Information, Virtual Learning Environments, Virtual Reality @article fusion-footer 9, author = fusion-footer 8, url = fusion-footer 7, doi = fusion-footer 6, issn = fusion-footer 5, year = fusion-footer 4, date = fusion-footer 3, journal = fusion-footer 2, publisher = fusion-footer 1, abstract = fusion-footer 0, note = wrapper 9, keywords = wrapper 8, pubstate = wrapper 7, tppubtype = wrapper 6 } This paper presents a systematic review of the literature on the modalities used in computer-based interventions (CBIs) and the impact of using these interventions in the learning, generalisation, and maintenance of language comprehension and decoding skills for children with autism spectrum disorder (ASD), ending with an appraisal of the certainty of evidence. Despite the importance of both skills in the reading comprehension and overall learning, a limited number of studies have been found. These include seven studies on language comprehension and seven studies on decoding. The shortlisted studies were analysed and a very limited number of modalities were found to have been used; text, graphics, audio, video, and mouse movement are used in all the studies and are termed basic modalities. Statistical analysis was also conducted on three parameters: (1) outcome of the study; (2) generalisation; and (3) maintenance. The analysis showed that CBIs were effective in facilitating these children’s learning; there was a significant improvement in the performance of children from the baseline to during and the post-intervention period. The analysis of generalisation has revealed positive results, indicating that the children were able to transfer information to a different setting or situation. Positive results are also noted from the analysis of maintenance, which indicate that the children retained information following the withdrawal of intervention. The combination of teachers’ instructions and CBI has provided better results than using either of them separately. This study has discovered 23 potential modalities and 2 potential CBIs including serious games and virtual learning environments that can be explored for language comprehension and decoding skills. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature. |
Hasan, C Z C; Jailani, R; Tahir, N M 2018-October , Institute of Electrical and Electronics Engineers Inc., 2019, ISSN: 21593442, (cited By 0). Abstract | Links | BibTeX | Tags: 10 Fold Cross Validation, 3D Modeling, Autism Spectrum Disorders, Biophysics, Clinical Decision Making, Computer Aided Diagnosis, Decision Making, Discriminant Analysis, Diseases, Gait Analysis, Gait Classification, Ground Reaction Forces, Neural Networks, Parameterization Techniques, Pattern Recognition, Petroleum Reservoir Evaluation, Program Diagnostics, Support Vector Machines, Targeted Treatment, Three-Dimensional @conference wrapper 5, author = wrapper 4, url = wrapper 3, doi = wrapper 2, issn = wrapper 1, year = wrapper 0, date = #boxed-wrapper 9, journal = #boxed-wrapper 8, volume = #boxed-wrapper 7, pages = #boxed-wrapper 6, publisher = #boxed-wrapper 5, abstract = #boxed-wrapper 4, note = #boxed-wrapper 3, keywords = #boxed-wrapper 2, pubstate = #boxed-wrapper 1, tppubtype = #boxed-wrapper 0 } Autism spectrum disorder (ASD) is a complex and lifelong neurodevelopmental condition that occurs in early childhood and is associated with unusual movement and gait disturbances. An automated and accurate recognition of ASD gait provides assistance in diagnosis and clinical decision-making as well as improving targeted treatment. This paper explores the use of two well-known machine learning classifiers, artificial neural network (ANN) and support vector machine (SVM) in distinguishing ASD and normal gait patterns based on prominent gait features derived from three-dimensional (3D) ground reaction forces (GRFs) data. The 3D GRFs data of 30 children with ASD and 30 typically developing children were obtained using two force plates during self-determined speed of barefoot walking. Time-series parameterization techniques were applied to the 3D GRFs waveforms to extract the significant gait features. The stepwise method of discriminant analysis (SWDA) was employed to determine the dominant GRF gait features in order to classify ASD and typically developing groups. The 10-fold cross-validation test results indicate that the ANN model with three dominant GRF input features outperformed the kernel-based SVM models with 93.3% accuracy, 96.7% sensitivity, and 90.0% specificity. The findings of this study demonstrate the reliability of using the 3D GRF input features, in combination with SWDA feature selection and ANN classification model as an appropriate method that may be beneficial for the diagnosis of ASD gait as well as for evaluation purpose of the treatment programs. © 2018 IEEE. |
Yap, C Y; Ng, K H; Cheah, Y; Lim, S Y; Price, J; Vries, De M App4Autism: An integrated assistive technology with heart rate monitoring for children with autism Journal Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11870 LNCS , pp. 498-512, 2019, ISSN: 03029743, (cited By 0). Abstract | Links | BibTeX | Tags: Assistive Technology, Autism, Diseases, Early Childhoods, Heart, Heart Rate Monitoring, Mobile Applications, Mobile Computing, Patient Monitoring @article Instagram Feed JS 9, author = Instagram Feed JS 8, editor = Instagram Feed JS 7, url = Instagram Feed JS 6, doi = Instagram Feed JS 5, issn = Instagram Feed JS 4, year = Instagram Feed JS 3, date = Instagram Feed JS 2, journal = Instagram Feed JS 1, volume = Instagram Feed JS 0, pages = {498-512}, publisher = {Springer}, abstract = {Autism Spectrum Disorder (ASD) is a neurological development disorder that affects communication and behavior. Most assistive technologies for children with autistic traits have been designed to support single, targeted activity function such as learning and communication. In this paper, we report the design and development of an assistive mobile application with heart rate monitoring to help children with ASD in their daily life activities. The integrated mobile application, App4Autism was developed using a holistic design approach with the aim of enhancing communication, interaction and learning skills while providing emotion regulation support through music listening and heart rate monitoring. A novel focus of App4Autism is on noise sensitivity; to play music upon automatic detection of loud excessive noise (in decibel) while at the same time, monitoring the user’s heart rate using a pulse sensor. The paper focuses on a study to better understand the potential use and incorporation of music listening and heart rate/anxiety level monitoring in the app. The paper provides results of investigation into which music genre is more suitable to keep users calm. Initial experiment involved a general population sample; with results showing that personal music preference might have calming effects on users in environments with excessive background noise. We further expand on the design guidelines for creating an integrated assistive technology. © Springer Nature Switzerland AG 2019.}, note = {cited By 0}, keywords = {Assistive Technology, Autism, Diseases, Early Childhoods, Heart, Heart Rate Monitoring, Mobile Applications, Mobile Computing, Patient Monitoring}, pubstate = {published}, tppubtype = {article} } Autism Spectrum Disorder (ASD) is a neurological development disorder that affects communication and behavior. Most assistive technologies for children with autistic traits have been designed to support single, targeted activity function such as learning and communication. In this paper, we report the design and development of an assistive mobile application with heart rate monitoring to help children with ASD in their daily life activities. The integrated mobile application, App4Autism was developed using a holistic design approach with the aim of enhancing communication, interaction and learning skills while providing emotion regulation support through music listening and heart rate monitoring. A novel focus of App4Autism is on noise sensitivity; to play music upon automatic detection of loud excessive noise (in decibel) while at the same time, monitoring the user’s heart rate using a pulse sensor. The paper focuses on a study to better understand the potential use and incorporation of music listening and heart rate/anxiety level monitoring in the app. The paper provides results of investigation into which music genre is more suitable to keep users calm. Initial experiment involved a general population sample; with results showing that personal music preference might have calming effects on users in environments with excessive background noise. We further expand on the design guidelines for creating an integrated assistive technology. © Springer Nature Switzerland AG 2019. |
Misman, M F; Samah, A A; Ezudin, F A; Majid, H A; Shah, Z A; Hashim, H; Harun, M F Classification of adults with autism spectrum disorder using deep neural network Conference Institute of Electrical and Electronics Engineers Inc., 2019, ISBN: 9781728130415, (cited By 0). Abstract | Links | BibTeX | Tags: Autism Spectrum Disorders, Brain Disorders, Classification (of information), Classification Accuracy, Classification Methods, Clinical Tests, Cognitive Skill, Computer Aided Diagnosis, Deep Learning, Deep Neural Networks, Diseases, Learning, Machine Learning Methods, Screening Data, Support Vector Machines @conference{Misman201929, title = {Classification of adults with autism spectrum disorder using deep neural network}, author = {M F Misman and A A Samah and F A Ezudin and H A Majid and Z A Shah and H Hashim and M F Harun}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079349811&doi=10.1109%2fAiDAS47888.2019.8970823&partnerID=40&md5=dd727e950667359680a6dbcc4855422f}, doi = {10.1109/AiDAS47888.2019.8970823}, isbn = {9781728130415}, year = {2019}, date = {2019-01-01}, journal = {Proceedings - 2019 1st International Conference on Artificial Intelligence and Data Sciences, AiDAS 2019}, pages = {29-34}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {Autism Spectrum Disorder (ASD) is a developmental brain disorder that causes deficits in linguistic, communicative, and cognitive skills as well as social skills. Various application of Machine Learning has been applied apart from the clinical tests available, which has increased the performance in the diagnosis of this disorder. In this study, we applied the Deep Neural Network (DNN) architecture, which has been a popular method in recent years and proved to improve classification accuracy. This study aims to analyse the performance of DNN model in the diagnosis of ASD in terms of classification accuracy by using two datasets of adult ASD screening data. The results are then compared with the previous Machine Learning method by another researcher, which is Support Vector Machine (SVM). The accuracy achieved by the DNN model in the classification of ASD diagnosis is 99.40% on the first dataset and achieved 96.08% on the second dataset. Meanwhile, the SVM model achieved an accuracy of 95.24% and 95.08% using the first and second data, respectively. The results show that ASD cases can be accurately identified by implementing the DNN classification method using ASD adult screening data. © 2019 IEEE.}, note = {cited By 0}, keywords = {Autism Spectrum Disorders, Brain Disorders, Classification (of information), Classification Accuracy, Classification Methods, Clinical Tests, Cognitive Skill, Computer Aided Diagnosis, Deep Learning, Deep Neural Networks, Diseases, Learning, Machine Learning Methods, Screening Data, Support Vector Machines}, pubstate = {published}, tppubtype = {conference} } Autism Spectrum Disorder (ASD) is a developmental brain disorder that causes deficits in linguistic, communicative, and cognitive skills as well as social skills. Various application of Machine Learning has been applied apart from the clinical tests available, which has increased the performance in the diagnosis of this disorder. In this study, we applied the Deep Neural Network (DNN) architecture, which has been a popular method in recent years and proved to improve classification accuracy. This study aims to analyse the performance of DNN model in the diagnosis of ASD in terms of classification accuracy by using two datasets of adult ASD screening data. The results are then compared with the previous Machine Learning method by another researcher, which is Support Vector Machine (SVM). The accuracy achieved by the DNN model in the classification of ASD diagnosis is 99.40% on the first dataset and achieved 96.08% on the second dataset. Meanwhile, the SVM model achieved an accuracy of 95.24% and 95.08% using the first and second data, respectively. The results show that ASD cases can be accurately identified by implementing the DNN classification method using ASD adult screening data. © 2019 IEEE. |
Khowaja, K; Salim, S S; Al-Thani, D Institute of Electrical and Electronics Engineers Inc., 2019, ISBN: 9781538679661, (cited By 2). Abstract | Links | BibTeX | Tags: Autism Spectrum Disorders, Components, Diseases, Framework, Game Design, Games, Serious Games, Vocabulary @conference{Khowaja2019, title = {Components to design serious games for children with autism spectrum disorder (ASD) to learn vocabulary}, author = {K Khowaja and S S Salim and D Al-Thani}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062890872&doi=10.1109%2fICETAS.2018.8629208&partnerID=40&md5=277d4ff732687855a21405bf66efe9af}, doi = {10.1109/ICETAS.2018.8629208}, isbn = {9781538679661}, year = {2019}, date = {2019-01-01}, journal = {2018 IEEE 5th International Conference on Engineering Technologies and Applied Sciences, ICETAS 2018}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {Background: The research on the use of serious games to provide learning of skills to children with autism spectrum disorder (ASD) has increased in recent years. The use of serious games to provide vocabulary learning to children with ASD is still in infancy stage. Serious games are designed using a framework as a basis to use components in the game. However, there is no existing serious game design framework that can consider the needs of children with ASD.Objective: The objective of this study is to review components that could be useful in the design of serious game for children with ASD to learn vocabulary.Methods: The review of the literature on vocabulary learning of children with ASD and existing SGDFs was carried out to identify the components. The components have been reviewed from the perspective of 1) vocabulary learning of children with ASD in particular, 2) children with ASD in whole, 3) typical children and 4) game design in general.Results: A total of fifty components were found. The four components namely autism behaviours, strategies, instruction methods and modalities are related to children with ASD and their learning of vocabulary. The remaining components are based on the review of existing SGDFs. There were similarities in terms of use of components across the frameworks.Conclusion: The analysis of these components in the serious games developed for children with ASD shows its usability in designing games for these children. © 2018 IEEE.}, note = {cited By 2}, keywords = {Autism Spectrum Disorders, Components, Diseases, Framework, Game Design, Games, Serious Games, Vocabulary}, pubstate = {published}, tppubtype = {conference} } Background: The research on the use of serious games to provide learning of skills to children with autism spectrum disorder (ASD) has increased in recent years. The use of serious games to provide vocabulary learning to children with ASD is still in infancy stage. Serious games are designed using a framework as a basis to use components in the game. However, there is no existing serious game design framework that can consider the needs of children with ASD.Objective: The objective of this study is to review components that could be useful in the design of serious game for children with ASD to learn vocabulary.Methods: The review of the literature on vocabulary learning of children with ASD and existing SGDFs was carried out to identify the components. The components have been reviewed from the perspective of 1) vocabulary learning of children with ASD in particular, 2) children with ASD in whole, 3) typical children and 4) game design in general.Results: A total of fifty components were found. The four components namely autism behaviours, strategies, instruction methods and modalities are related to children with ASD and their learning of vocabulary. The remaining components are based on the review of existing SGDFs. There were similarities in terms of use of components across the frameworks.Conclusion: The analysis of these components in the serious games developed for children with ASD shows its usability in designing games for these children. © 2018 IEEE. |
Abdullah, A A; Rijal, S; Dash, S R Evaluation on Machine Learning Algorithms for Classification of Autism Spectrum Disorder (ASD) Conference 1372 (1), Institute of Physics Publishing, 2019, ISSN: 17426588, (cited By 0). Abstract | Links | BibTeX | Tags: Autism Spectrum Disorders, Behaviour Evaluations, Biomedical Engineering, Brain Mapping, Classification (of information), Decision Trees, Diseases, Feature Extraction, Feature Selection Methods, K Fold Cross Validations, Learning, Least Absolute Shrinkage and Selection Operators, Least Squares Approximations, Logistic Regressions, Machine Learning, Machine Learning Methods, Magnetic Resonance Imaging, Nearest Neighbor Search, Regression Analysis, Supervised Learning, Supervised Machine Learning @conference{Abdullah2019, title = {Evaluation on Machine Learning Algorithms for Classification of Autism Spectrum Disorder (ASD)}, author = {A A Abdullah and S Rijal and S R Dash}, editor = {Rahim Mustafa Zaaba Norali Noor S B A N B S K A N B A B M Fook C.Y. Yazid H.B.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076493636&doi=10.1088%2f1742-6596%2f1372%2f1%2f012052&partnerID=40&md5=2ec1bd9f6cf1e3afe965cc9e3792f536}, doi = {10.1088/1742-6596/1372/1/012052}, issn = {17426588}, year = {2019}, date = {2019-01-01}, journal = {Journal of Physics: Conference Series}, volume = {1372}, number = {1}, publisher = {Institute of Physics Publishing}, abstract = {Autism Spectrum Disorder (ASD) was characterized by delay in social interactions development, repetitive behaviors and narrow interest, which usually diagnosed with standard diagnostic tools such as Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview-Revised (ADIR-R). Previous work has implemented machine-learning methods for the classification of ASD, however they used different types of dataset such as brain images for MRI and EEG, risk genes in genetic profiles and behavior evaluation based on ADOS and ADI-R. Here a trial on using Autism Spectrum Questions (AQ) to build models that have higher potential to classify ASD was developed. In this research, Chi-square and Least Absolute Shrinkage and Selection Operator (LASSO) have been selected as feature selection methods to select the most important features for 3 supervised machine learning algorithms, which are Random Forest, Logistic Regression and K-Nearest Neighbors with K-fold cross validation. The performance was evaluated in which results Logistic Regression scored the highest accuracy with 97.541% using model with 13 selected features based on Chi-square selection method. © 2019 IOP Publishing Ltd. All rights reserved.}, note = {cited By 0}, keywords = {Autism Spectrum Disorders, Behaviour Evaluations, Biomedical Engineering, Brain Mapping, Classification (of information), Decision Trees, Diseases, Feature Extraction, Feature Selection Methods, K Fold Cross Validations, Learning, Least Absolute Shrinkage and Selection Operators, Least Squares Approximations, Logistic Regressions, Machine Learning, Machine Learning Methods, Magnetic Resonance Imaging, Nearest Neighbor Search, Regression Analysis, Supervised Learning, Supervised Machine Learning}, pubstate = {published}, tppubtype = {conference} } Autism Spectrum Disorder (ASD) was characterized by delay in social interactions development, repetitive behaviors and narrow interest, which usually diagnosed with standard diagnostic tools such as Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview-Revised (ADIR-R). Previous work has implemented machine-learning methods for the classification of ASD, however they used different types of dataset such as brain images for MRI and EEG, risk genes in genetic profiles and behavior evaluation based on ADOS and ADI-R. Here a trial on using Autism Spectrum Questions (AQ) to build models that have higher potential to classify ASD was developed. In this research, Chi-square and Least Absolute Shrinkage and Selection Operator (LASSO) have been selected as feature selection methods to select the most important features for 3 supervised machine learning algorithms, which are Random Forest, Logistic Regression and K-Nearest Neighbors with K-fold cross validation. The performance was evaluated in which results Logistic Regression scored the highest accuracy with 97.541% using model with 13 selected features based on Chi-square selection method. © 2019 IOP Publishing Ltd. All rights reserved. |
2018 |
Basir, N; Hashim, A F M; Abdullah, S; Rahim, N A A; Sabri, M; Yusuf, A H; Harun, W N; Buragohain, D 150 , EDP Sciences, 2018, ISSN: 2261236X, (cited By 0). Abstract | Links | BibTeX | Tags: Application Programs, Articulation Points, Autistic Children, Children with Autism, Diseases, Distributed Computer Systems, Human Development, Linguistics, Malay Languages, Malaysia, Reading Comprehension, Reading Skills, Software Applications, Touchscreens @conference{Basir2018, title = {"talking Phonics for Autism": Developing a multi-purpose touch screen technology software application which utilizes sound articulation point to teach autistic children}, author = {N Basir and A F M Hashim and S Abdullah and N A A Rahim and M Sabri and A H Yusuf and W N Harun and D Buragohain}, editor = {Mohd Salleh M A A Aljunid Syed Junid S.A. Rashidi C.B.M.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054012883&doi=10.1051%2fmatecconf%2f201815005040&partnerID=40&md5=d0cb0e71818be5cd02d2b28e936f45d7}, doi = {10.1051/matecconf/201815005040}, issn = {2261236X}, year = {2018}, date = {2018-01-01}, journal = {MATEC Web of Conferences}, volume = {150}, publisher = {EDP Sciences}, abstract = {This paper aims to examine the potentials of the multi-purpose touch screen technology application which utilizes a sound articulation point software called "TALKING PHONICS FOR AUTISMäs an alternative method of teaching phonics to autistic children. "TALKING PHONICS FOR AUTISM"is developed via a collaborative effort between the Centre of International Languages (CIL) and the School of Human Development and techno Communication (iKOM), University Malaysia Perlis (UniMAP). The reading skills of autism children are developed intofive (5) levels ofMalay reading comprehension skills. The first level consists of open syllables - vowels and consonants. The following consecutivethree levels comprised of closed syllables. The fourth level introduces vocal sequence while the fifth level constitutes of Malay language loans. The Malay-language dialect phonological theory by Tajul Aripin Kassin (2000) which is based on Clements & Keysher's (1980) Generative Booking Generic Fonology Model (CV) forms the theorectical framework of this paper. © 2017 The Authors.}, note = {cited By 0}, keywords = {Application Programs, Articulation Points, Autistic Children, Children with Autism, Diseases, Distributed Computer Systems, Human Development, Linguistics, Malay Languages, Malaysia, Reading Comprehension, Reading Skills, Software Applications, Touchscreens}, pubstate = {published}, tppubtype = {conference} } This paper aims to examine the potentials of the multi-purpose touch screen technology application which utilizes a sound articulation point software called "TALKING PHONICS FOR AUTISMäs an alternative method of teaching phonics to autistic children. "TALKING PHONICS FOR AUTISM"is developed via a collaborative effort between the Centre of International Languages (CIL) and the School of Human Development and techno Communication (iKOM), University Malaysia Perlis (UniMAP). The reading skills of autism children are developed intofive (5) levels ofMalay reading comprehension skills. The first level consists of open syllables - vowels and consonants. The following consecutivethree levels comprised of closed syllables. The fourth level introduces vocal sequence while the fifth level constitutes of Malay language loans. The Malay-language dialect phonological theory by Tajul Aripin Kassin (2000) which is based on Clements & Keysher's (1980) Generative Booking Generic Fonology Model (CV) forms the theorectical framework of this paper. © 2017 The Authors. |
Ghazali, R; Soon, C C; Hassan, S N S; Sulaiman, N Design and development of therapeutic aid tools using human-machine interaction approach for children with autism spectrum disorder Journal Article Advances in Intelligent Systems and Computing, 739 , pp. 530-537, 2018, ISSN: 21945357, (cited By 0). Abstract | Links | BibTeX | Tags: Autism Spectrum Disorders, Children with Autism, Communication Skills, Design and Development, Diseases, Economic and Social Effects, Human Machine Interaction, Human Robot Interaction, Learning, Man Machine Systems, Patient Rehabilitation, Robotics, Social Interactions, Technology Enhancements @article{Ghazali2018530, title = {Design and development of therapeutic aid tools using human-machine interaction approach for children with autism spectrum disorder}, author = {R Ghazali and C C Soon and S N S Hassan and N Sulaiman}, editor = {Levy Mohd Lokman Chen P A K Koyama S. Yamanaka T.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044232513&doi=10.1007%2f978-981-10-8612-0_55&partnerID=40&md5=94310d263566c262486065187e7d4f09}, doi = {10.1007/978-981-10-8612-0_55}, issn = {21945357}, year = {2018}, date = {2018-01-01}, journal = {Advances in Intelligent Systems and Computing}, volume = {739}, pages = {530-537}, publisher = {Springer Verlag}, abstract = {The development of human–machine interaction as teaching and therapeutic aid tools for therapist as well as parents of children with various levels of autism spectrum disorder (ASD) has been widely developed amongst the researchers and academician. The technology enhancement by integrating robotics and automation is purposely established to provide assistance for children with ASD that suffer from brain development, social interaction, communication skill, and cognitive function. Therefore, this paper presents the development and evaluation of the therapeutic aid tools through human-machine interaction approaches. Apart from attracting the children with ASD to participate in rehabilitation and learning process, these tools are purposely designed to encourage children with ASD to learn and react using the various interactive physical games. In the evaluation process, the completion time has been recorded in the continuation of three attempts for the comparison purpose. As a result, the combination of technology in this therapeutic aid tools will enhance the level of thinking and elevate the activities during the therapy process. As a conclusion, different methods can be enhanced to support children with ASD through the existing technologies and thus provide new alternatives in therapy process. © Springer Nature Singapore Pte Ltd. 2018.}, note = {cited By 0}, keywords = {Autism Spectrum Disorders, Children with Autism, Communication Skills, Design and Development, Diseases, Economic and Social Effects, Human Machine Interaction, Human Robot Interaction, Learning, Man Machine Systems, Patient Rehabilitation, Robotics, Social Interactions, Technology Enhancements}, pubstate = {published}, tppubtype = {article} } The development of human–machine interaction as teaching and therapeutic aid tools for therapist as well as parents of children with various levels of autism spectrum disorder (ASD) has been widely developed amongst the researchers and academician. The technology enhancement by integrating robotics and automation is purposely established to provide assistance for children with ASD that suffer from brain development, social interaction, communication skill, and cognitive function. Therefore, this paper presents the development and evaluation of the therapeutic aid tools through human-machine interaction approaches. Apart from attracting the children with ASD to participate in rehabilitation and learning process, these tools are purposely designed to encourage children with ASD to learn and react using the various interactive physical games. In the evaluation process, the completion time has been recorded in the continuation of three attempts for the comparison purpose. As a result, the combination of technology in this therapeutic aid tools will enhance the level of thinking and elevate the activities during the therapy process. As a conclusion, different methods can be enhanced to support children with ASD through the existing technologies and thus provide new alternatives in therapy process. © Springer Nature Singapore Pte Ltd. 2018. |
Azahari, Ahmad I N N B; Ahmad, Wan W F; Hashim, A S Evaluation of video modeling application to teach social interaction skills to autistic children Journal Article Communications in Computer and Information Science, 886 , pp. 125-135, 2018, ISSN: 18650929, (cited By 0). Abstract | Links | BibTeX | Tags: Autism Spectrum Disorders, Autistic Children, Children with Autism, Communication Skills, Computer, Computer Science, Diseases, Learning Materials, Mental Disorders, Mobile Applications, Mobile Technology, Social Interactions @article{AhmadAzahari2018125, title = {Evaluation of video modeling application to teach social interaction skills to autistic children}, author = {I N N B Ahmad Azahari and W F Wan Ahmad and A S Hashim}, editor = {Foth M Abdullah N. Wan Adnan W.A.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052957663&doi=10.1007%2f978-981-13-1628-9_12&partnerID=40&md5=25564063d73e43461ac32389f19c9e05}, doi = {10.1007/978-981-13-1628-9_12}, issn = {18650929}, year = {2018}, date = {2018-01-01}, journal = {Communications in Computer and Information Science}, volume = {886}, pages = {125-135}, publisher = {Springer Verlag}, abstract = {Autism Social Aid (ASD) is a mental disorder that affects a person at an early age. People with ASD show deficiencies in daily living abilities that lead to impairment in their independence skill, restrict their social involvement which leads to poor living style. This rooted from their key personal behaviours, which are impairment in social and communication skills. However, with the availability of mobile technology that engages education through video modelling, it has become more practical for educators to train daily living skills for individuals with ASD. Consequently a Video Modelling Application called ‘Autism Social-Aid’ was created to provide a supplementary learning material envisioned to help stimulate children with ASD in the learning process. The purpose of this study is to evaluate the effects of video modelling in teaching five children diagnosed with medium-functioning ASD to understand social interaction skills. The children went through three trials of the evaluation phases. Results revealed that video modelling was effective as all of the children were able to display positive improvements from the first trial to the third trial. As a result, all of them have reduced an average 77% of the total prompt needed to remain focus on the video lesson and an average of 70% number of errors was reduced during the quiz evaluation. © 2018, Springer Nature Singapore Pte Ltd.}, note = {cited By 0}, keywords = {Autism Spectrum Disorders, Autistic Children, Children with Autism, Communication Skills, Computer, Computer Science, Diseases, Learning Materials, Mental Disorders, Mobile Applications, Mobile Technology, Social Interactions}, pubstate = {published}, tppubtype = {article} } Autism Social Aid (ASD) is a mental disorder that affects a person at an early age. People with ASD show deficiencies in daily living abilities that lead to impairment in their independence skill, restrict their social involvement which leads to poor living style. This rooted from their key personal behaviours, which are impairment in social and communication skills. However, with the availability of mobile technology that engages education through video modelling, it has become more practical for educators to train daily living skills for individuals with ASD. Consequently a Video Modelling Application called ‘Autism Social-Aid’ was created to provide a supplementary learning material envisioned to help stimulate children with ASD in the learning process. The purpose of this study is to evaluate the effects of video modelling in teaching five children diagnosed with medium-functioning ASD to understand social interaction skills. The children went through three trials of the evaluation phases. Results revealed that video modelling was effective as all of the children were able to display positive improvements from the first trial to the third trial. As a result, all of them have reduced an average 77% of the total prompt needed to remain focus on the video lesson and an average of 70% number of errors was reduced during the quiz evaluation. © 2018, Springer Nature Singapore Pte Ltd. |
2017 |
Dzulkifli, M A; Wahdi, E V F A; Rahman, A W A Institute of Electrical and Electronics Engineers Inc., 2017, ISBN: 9781509045211, (cited By 3). Abstract | Links | BibTeX | Tags: Autism Spectrum Disorders, Children with Autism, Computer Aided Instruction, Computer Assisted Instruction, Diseases, E-learning, Education, Educational Strategy, Language Development, Pervasive Developmental Disorders, Teaching, Vocabulary Learning, Well Intervention @conference{Dzulkifli201747, title = {A review for future research and practice in using computer assisted instruction on vocabulary learning among children with autism spectrum disorder}, author = {M A Dzulkifli and E V F A Wahdi and A W A Rahman}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013059526&doi=10.1109%2fICT4M.2016.21&partnerID=40&md5=c78e01f1ebd8c062011d42d8853ce4fd}, doi = {10.1109/ICT4M.2016.21}, isbn = {9781509045211}, year = {2017}, date = {2017-01-01}, journal = {Proceedings - 6th International Conference on Information and Communication Technology for the Muslim World, ICT4M 2016}, pages = {47-52}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {A lack of educational strategies may hinder students from benefiting the most from their education. The existing public or government schools do not adequately accommodate children with special needs in terms of providing them with good syllabuses as well interventions. Instead, various forms of pervasive developmental disorders are frequently placed in special education classes without an accurate diagnosis. This is something that needs to be rectified because every disability requires different needs and attention. In children with special needs such as children with Autism Spectrum Disorder (ASD), it warrants diverse teaching methods to be used. While the use of computer assisted instructions (CAIs) in the West has been found to be effective for children with ASD, research regarding the applicability of CAIs to cater for the learning process of children with special needs in the Malaysian context is still lacking. The present paper reviews previous studies that have employed CAIs to enhance language development of children with ASD. Following this, it recommends future research that incorporates the use of CAI to improve vocabulary learning of children with ASD who are non-native English speakers. © 2016 IEEE.}, note = {cited By 3}, keywords = {Autism Spectrum Disorders, Children with Autism, Computer Aided Instruction, Computer Assisted Instruction, Diseases, E-learning, Education, Educational Strategy, Language Development, Pervasive Developmental Disorders, Teaching, Vocabulary Learning, Well Intervention}, pubstate = {published}, tppubtype = {conference} } A lack of educational strategies may hinder students from benefiting the most from their education. The existing public or government schools do not adequately accommodate children with special needs in terms of providing them with good syllabuses as well interventions. Instead, various forms of pervasive developmental disorders are frequently placed in special education classes without an accurate diagnosis. This is something that needs to be rectified because every disability requires different needs and attention. In children with special needs such as children with Autism Spectrum Disorder (ASD), it warrants diverse teaching methods to be used. While the use of computer assisted instructions (CAIs) in the West has been found to be effective for children with ASD, research regarding the applicability of CAIs to cater for the learning process of children with special needs in the Malaysian context is still lacking. The present paper reviews previous studies that have employed CAIs to enhance language development of children with ASD. Following this, it recommends future research that incorporates the use of CAI to improve vocabulary learning of children with ASD who are non-native English speakers. © 2016 IEEE. |
Hashim, R; Yussof, H A Review of the Ambit of Politics in Social Robotics Conference 105 , Elsevier B.V., 2017, ISSN: 18770509, (cited By 3). Abstract | Links | BibTeX | Tags: Acceptance, Autism, Children, Diseases, Economic and Social Effects, Education, Influence, Intelligent Control, Machine Design, Politics, Robotics, Robots, Smart Sensors, Social Robotics, Social Sciences @conference{Hashim2017316, title = {A Review of the Ambit of Politics in Social Robotics}, author = {R Hashim and H Yussof}, editor = {Yussof H.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016116583&doi=10.1016%2fj.procs.2017.01.228&partnerID=40&md5=d87a64238e7afb117359db4af16a4b52}, doi = {10.1016/j.procs.2017.01.228}, issn = {18770509}, year = {2017}, date = {2017-01-01}, journal = {Procedia Computer Science}, volume = {105}, pages = {316-321}, publisher = {Elsevier B.V.}, abstract = {This article reviews the range of currently held positions on the politics of social robotics for skill augmentation of children with autism and other brain disabilities. Publications from peer-reviewed journals and conference proceedings were analyzed. From these articles categorizations were accorded into three emerging themes on the politics of social robotics which are, influence, acceptance and adoption. The findings indicated that the social skilling of brain-impaired children are implicated but not present in the development and design process of the robots. Instead, the human social skills were assigned to the capability and general features of the robots. The need for social robots is in tandem with societal changes and the increased demographics as well as demands from the healthcare industry. The conceptualization of brain-impaired children is plagued with stereotypical views that they are both mentally and physically handicapped, helpless, require round-the-clock care and in need of robotic assistance when humans fail. Depending on the nation status, the influence, acceptance and adoption of social robotics are indeed political and the success of science for society needs has to be re-examined and perhaps redefined in order to reap the return on investment of the robot production. © 2017 The Authors.}, note = {cited By 3}, keywords = {Acceptance, Autism, Children, Diseases, Economic and Social Effects, Education, Influence, Intelligent Control, Machine Design, Politics, Robotics, Robots, Smart Sensors, Social Robotics, Social Sciences}, pubstate = {published}, tppubtype = {conference} } This article reviews the range of currently held positions on the politics of social robotics for skill augmentation of children with autism and other brain disabilities. Publications from peer-reviewed journals and conference proceedings were analyzed. From these articles categorizations were accorded into three emerging themes on the politics of social robotics which are, influence, acceptance and adoption. The findings indicated that the social skilling of brain-impaired children are implicated but not present in the development and design process of the robots. Instead, the human social skills were assigned to the capability and general features of the robots. The need for social robots is in tandem with societal changes and the increased demographics as well as demands from the healthcare industry. The conceptualization of brain-impaired children is plagued with stereotypical views that they are both mentally and physically handicapped, helpless, require round-the-clock care and in need of robotic assistance when humans fail. Depending on the nation status, the influence, acceptance and adoption of social robotics are indeed political and the success of science for society needs has to be re-examined and perhaps redefined in order to reap the return on investment of the robot production. © 2017 The Authors. |
Shminan, A S; Adzani, R A; Sharif, S; Lee, N K 2018-January , Institute of Electrical and Electronics Engineers Inc., 2017, ISBN: 9781538607657, (cited By 1). Abstract | Links | BibTeX | Tags: Autism, Autism Spectrum Disorders, Behavioral Disabilities, Diseases, Drones, E-learning, Human Computer Interaction, Intervention, Mobile Based Learning, Mobile Computing, Parents, Surveys, Systems Analysis, Technology Transfer, User Interface Designs, User Interfaces @conference{Shminan201749, title = {AutiPECS: Mobile based learning of picture exchange communication intervention for caregivers of autistic children}, author = {A S Shminan and R A Adzani and S Sharif and N K Lee}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050617137&doi=10.1109%2fICONDA.2017.8270398&partnerID=40&md5=67a6c94341aa3b530fede19c93a63d81}, doi = {10.1109/ICONDA.2017.8270398}, isbn = {9781538607657}, year = {2017}, date = {2017-01-01}, journal = {1st International Conference on Computer and Drone Applications: Ethical Integration of Computer and Drone Technology for Humanity Sustainability, IConDA 2017}, volume = {2018-January}, pages = {49-54}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {The aim of this study is to develop and assess a mobile-based learning concerning the Picture Exchange Communication (PECS) for Autism Spectrum Disorder (ASD) children's caregivers. Being an inexpensive intervention, the PECS has been proposed by other parents who have practised it on their children with non-verbal and behavioral disabilities. The underlying motivator for this mobile application is to guarantee that autistic children can have a better alternative intervention through the PECS approach so that they would not rely on the therapist a great deal or go to the autism center which is often costly. This mobile application elaborates on the user requirements which include PECS introduction, the characteristics, initial preparations, strategies and the activities. Instructional System Design (ISD) functions as the methodologies that help create the mobile-based learning. The system design has five stages namely the analysis, design, development, implementation and evaluation. These stages are better known as ADDIE which ensure the user to attain the goals of the instruction for the entire process. To examine the content and the user interface design for this mobile application, a formative evaluation was conducted which was aided by the usability testing by questionnaires and short instructed interviews. With the application of the ADDIE principles and guideline of Human-Computer Interaction (HCI), the best combination of causes of the AutiPECS had been developed properly. In sum, this research has achieved the objectives. The content had been assessed by the expert, and the caregivers know how to adopt D.I.Y concepts as they are working on the learning materials. Future works may also be able to take more advantage of the AutiPECS 2.0 version where they can develop the mobile-based learning of PECS in the extended content and pay more attention to more specific case studies so that the caregivers know how to use PECS with the special children everyday. © 2017 IEEE.}, note = {cited By 1}, keywords = {Autism, Autism Spectrum Disorders, Behavioral Disabilities, Diseases, Drones, E-learning, Human Computer Interaction, Intervention, Mobile Based Learning, Mobile Computing, Parents, Surveys, Systems Analysis, Technology Transfer, User Interface Designs, User Interfaces}, pubstate = {published}, tppubtype = {conference} } The aim of this study is to develop and assess a mobile-based learning concerning the Picture Exchange Communication (PECS) for Autism Spectrum Disorder (ASD) children's caregivers. Being an inexpensive intervention, the PECS has been proposed by other parents who have practised it on their children with non-verbal and behavioral disabilities. The underlying motivator for this mobile application is to guarantee that autistic children can have a better alternative intervention through the PECS approach so that they would not rely on the therapist a great deal or go to the autism center which is often costly. This mobile application elaborates on the user requirements which include PECS introduction, the characteristics, initial preparations, strategies and the activities. Instructional System Design (ISD) functions as the methodologies that help create the mobile-based learning. The system design has five stages namely the analysis, design, development, implementation and evaluation. These stages are better known as ADDIE which ensure the user to attain the goals of the instruction for the entire process. To examine the content and the user interface design for this mobile application, a formative evaluation was conducted which was aided by the usability testing by questionnaires and short instructed interviews. With the application of the ADDIE principles and guideline of Human-Computer Interaction (HCI), the best combination of causes of the AutiPECS had been developed properly. In sum, this research has achieved the objectives. The content had been assessed by the expert, and the caregivers know how to adopt D.I.Y concepts as they are working on the learning materials. Future works may also be able to take more advantage of the AutiPECS 2.0 version where they can develop the mobile-based learning of PECS in the extended content and pay more attention to more specific case studies so that the caregivers know how to use PECS with the special children everyday. © 2017 IEEE. |
Ilias, S; Tahir, N M; Jailani, R Development of three dimensional gait pattern in autism children - a review Conference Institute of Electrical and Electronics Engineers Inc., 2017, ISBN: 9781509011780, (cited By 0). Abstract | Links | BibTeX | Tags: Abnormal Gait, Children with Autism, Clinical Decision Making, Control Systems, Decision Making, Diseases, Enzyme Kinetics, Gait Analysis, Gait Classification, Kinematics, Spatial Temporals, Temporal Spatial, Three-Dimensional, Three-Dimensional Computer Graphics, Treatment Planning @conference{Ilias2017540, title = {Development of three dimensional gait pattern in autism children - a review}, author = {S Ilias and N M Tahir and R Jailani}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019000981&doi=10.1109%2fICCSCE.2016.7893635&partnerID=40&md5=37aaf5f94b177ecfa164c432d32b5dfe}, doi = {10.1109/ICCSCE.2016.7893635}, isbn = {9781509011780}, year = {2017}, date = {2017-01-01}, journal = {Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016}, pages = {540-545}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {Recently, gait patterns of children with autism is of interest in the gait community in order to identify significant gait parameter namely the three dimensional (3D) gait features such as spatial temporal, kinematic and kinetic. This is because gait pattern provides clinicians and researchers in understanding the trajectory of gait development. Understanding the characteristics and identifying gait pattern is essential in order to distinguish normal as well as abnormal gait pattern. Hence the purpose of this review is to identify deviations gait in children with autism based on criteria specifically subject character; measurement, type of gait variables measured; method of classification and major findings. Several gait variables from different instrumentation for gait analysis is reviewed too. Development of gait patterns via assessing gait deviations in children with ASD could assist clinician and researchers to differentiate gait pattern abnormality in diagnosing, clinical decision-making and treatment planning as well. © 2016 IEEE.}, note = {cited By 0}, keywords = {Abnormal Gait, Children with Autism, Clinical Decision Making, Control Systems, Decision Making, Diseases, Enzyme Kinetics, Gait Analysis, Gait Classification, Kinematics, Spatial Temporals, Temporal Spatial, Three-Dimensional, Three-Dimensional Computer Graphics, Treatment Planning}, pubstate = {published}, tppubtype = {conference} } Recently, gait patterns of children with autism is of interest in the gait community in order to identify significant gait parameter namely the three dimensional (3D) gait features such as spatial temporal, kinematic and kinetic. This is because gait pattern provides clinicians and researchers in understanding the trajectory of gait development. Understanding the characteristics and identifying gait pattern is essential in order to distinguish normal as well as abnormal gait pattern. Hence the purpose of this review is to identify deviations gait in children with autism based on criteria specifically subject character; measurement, type of gait variables measured; method of classification and major findings. Several gait variables from different instrumentation for gait analysis is reviewed too. Development of gait patterns via assessing gait deviations in children with ASD could assist clinician and researchers to differentiate gait pattern abnormality in diagnosing, clinical decision-making and treatment planning as well. © 2016 IEEE. |
Kamaruzaman, M F; Noor, H M; Hanapiah, F A; Azahari, M H H Efficacy of DTT by using touchscreen learning numeracy App for children with autism Conference Institute of Electrical and Electronics Engineers Inc., 2017, ISBN: 9781509015955, (cited By 1). Abstract | Links | BibTeX | Tags: Application Design, Behaviour Analysis, Cause and Effects, Children with Autism, Computer Aided Instruction, Diseases, E-learning, Education, Engineering Education, Interactive Learning, Learning, Scaffolds, Statistics, Teaching, Windows Platform @conference{Kamaruzaman2017198, title = {Efficacy of DTT by using touchscreen learning numeracy App for children with autism}, author = {M F Kamaruzaman and H M Noor and F A Hanapiah and M H H Azahari}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015855570&doi=10.1109%2fICEED.2016.7856071&partnerID=40&md5=7c8bf72171f0671937980837ef25a7cf}, doi = {10.1109/ICEED.2016.7856071}, isbn = {9781509015955}, year = {2017}, date = {2017-01-01}, journal = {2016 IEEE 8th International Conference on Engineering Education: Enhancing Engineering Education Through Academia-Industry Collaboration, ICEED 2016}, pages = {198-201}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {Touchscreen assistive learning numeracy application (TaLNA) is a touchscreen learning based application design for Children with Autism. TaLNA has been developed based on the concept of Applied Behaviour Analysis (ABA) called discrete trial training (DTT). This app will be used by teachers and instructors as a platform to facilitate children with autism on learning basic numeracy development in special schools. Thus, this study will investigate the efficacy and the effect of touchscreen assistive learning towards the children with autism. This app will run on Android and Windows platform. At an economical price range, the touchscreen assistive learning will have an immediate cause and effect response that enables the children with autism to be more independent during the scaffolds learning process. Hence it is an essence enhancement for children with autism management in and outside the classroom. This app is embedded with animated and interactive learning which has the potential to keep the children with autism motivated and engaged. It is a hope that TaLNA may inspire the instructional learning environment for children with autism, which could avail boost in early childcare education (ECCE). © 2016 IEEE.}, note = {cited By 1}, keywords = {Application Design, Behaviour Analysis, Cause and Effects, Children with Autism, Computer Aided Instruction, Diseases, E-learning, Education, Engineering Education, Interactive Learning, Learning, Scaffolds, Statistics, Teaching, Windows Platform}, pubstate = {published}, tppubtype = {conference} } Touchscreen assistive learning numeracy application (TaLNA) is a touchscreen learning based application design for Children with Autism. TaLNA has been developed based on the concept of Applied Behaviour Analysis (ABA) called discrete trial training (DTT). This app will be used by teachers and instructors as a platform to facilitate children with autism on learning basic numeracy development in special schools. Thus, this study will investigate the efficacy and the effect of touchscreen assistive learning towards the children with autism. This app will run on Android and Windows platform. At an economical price range, the touchscreen assistive learning will have an immediate cause and effect response that enables the children with autism to be more independent during the scaffolds learning process. Hence it is an essence enhancement for children with autism management in and outside the classroom. This app is embedded with animated and interactive learning which has the potential to keep the children with autism motivated and engaged. It is a hope that TaLNA may inspire the instructional learning environment for children with autism, which could avail boost in early childcare education (ECCE). © 2016 IEEE. |
Senan, N; Aziz, Wan Ab W A; Othman, M F; Suparjoh, S 135 , EDP Sciences, 2017, ISSN: 2261236X, (cited By 1). Abstract | Links | BibTeX | Tags: Al-Quran, Aluminum, Children with Autism, Diseases, Learning, Learning Materials, Main Module, Manufacture, Mobile Applications, Mobile Computing, Mobile Telecommunication Systems, Teaching, User Testing @conference{Senan2017, title = {Embedding Repetition (Takrir) Technique in Developing Al-Quran Memorizing Mobile Application for Autism Children}, author = {N Senan and W A Wan Ab Aziz and M F Othman and S Suparjoh}, editor = {Sofian Amir Mohd Faizal Izzuddin Mohd Rasidi Mohd Azlis Sani Md.J. Ahmad Mubarak M K M B Z I T A Nik Hisyamudin M.N. Al Emran I.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85036457592&doi=10.1051%2fmatecconf%2f201713500076&partnerID=40&md5=89a8a813a3f2af36f46870c9b4f4dd39}, doi = {10.1051/matecconf/201713500076}, issn = {2261236X}, year = {2017}, date = {2017-01-01}, journal = {MATEC Web of Conferences}, volume = {135}, publisher = {EDP Sciences}, abstract = {Nowadays, there are various types of learning materials used in the process of teaching and learning of Al-Quran including the use of mobile application. However, the features of mobile application that are appropriate for the process of memorizing the Al-Quran, especially for the needs of children with autism is still limited. Thus, this paper proposes an interactive Al-Quran mobile application namely iHafaz to facilitate autism children recite and memorizing Al-Quran. A takrir (repetition) technique in Islamic learning approach is embedded in this mobile application in order to assist autism children memorizing the Al-Quran easily. This mobile application consists of two main modules which are Hafaz (Memorize) and Latihan (Exercise). Result from the user testing shows that 72.4% of respondents agree that the takrir technique embedded in the mobile application able to improve the usability of the mobile application in helping the autism children to recite and memorize the Al-Quran easily. © 2017 The Authors.}, note = {cited By 1}, keywords = {Al-Quran, Aluminum, Children with Autism, Diseases, Learning, Learning Materials, Main Module, Manufacture, Mobile Applications, Mobile Computing, Mobile Telecommunication Systems, Teaching, User Testing}, pubstate = {published}, tppubtype = {conference} } Nowadays, there are various types of learning materials used in the process of teaching and learning of Al-Quran including the use of mobile application. However, the features of mobile application that are appropriate for the process of memorizing the Al-Quran, especially for the needs of children with autism is still limited. Thus, this paper proposes an interactive Al-Quran mobile application namely iHafaz to facilitate autism children recite and memorizing Al-Quran. A takrir (repetition) technique in Islamic learning approach is embedded in this mobile application in order to assist autism children memorizing the Al-Quran easily. This mobile application consists of two main modules which are Hafaz (Memorize) and Latihan (Exercise). Result from the user testing shows that 72.4% of respondents agree that the takrir technique embedded in the mobile application able to improve the usability of the mobile application in helping the autism children to recite and memorize the Al-Quran easily. © 2017 The Authors. |
Ilias, S; Tahir, N M; Jailani, R Institute of Electrical and Electronics Engineers Inc., 2017, ISBN: 9781509009251, (cited By 0). Abstract | Links | BibTeX | Tags: Classification (of information), Discriminant Analysis, Diseases, Extraction, Feature Extraction, Gait Analysis, Gait Classification, Image Retrieval, Industrial Electronics, Kernel Function, Kinematic Parameters, Kinematics, Learning, Linear Discriminant Analysis, Machine Learning Approaches, Motion Analysis System, Polynomial Functions, Principal Component Analysis, Support Vector Machines, SVM Classifiers @conference{Ilias2017275, title = {Feature extraction of autism gait data using principal component analysis and linear discriminant analysis}, author = {S Ilias and N M Tahir and R Jailani}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85034081031&doi=10.1109%2fIEACON.2016.8067391&partnerID=40&md5=7deaef6538413df7bfaf7cf723001d72}, doi = {10.1109/IEACON.2016.8067391}, isbn = {9781509009251}, year = {2017}, date = {2017-01-01}, journal = {IEACon 2016 - 2016 IEEE Industrial Electronics and Applications Conference}, pages = {275-279}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {In this research, the application of machine learning approach specifically support vector machine along with principal component analysis and linear discriminant analysis as feature extractions are evaluated and validated in discriminating gait features between normal subjects and autism children. Gait features of 32 normal and 12 autism children were recorded and analyzed using VICON motion analysis system and a force platform during normal walking. Here, twenty one gait features describing the three types of gait characteristics namely basic, kinetic and kinematic in these children are extracted. Further, with these gait features as input during classification, the ability of SVM as classifier are investigated using three different kernel functions specifically linear, polynomial, and radial basis. Results showed that LDA as feature extraction is the highest accuracy with kinematic parameters as gait features along with polynomial function as kernel for the SVM classifier. This finding proven that LDA is suitable as feature extraction and SVM is indeed apt as gait classifier in classifying the gait pattern autism and normal children. © 2016 IEEE.}, note = {cited By 0}, keywords = {Classification (of information), Discriminant Analysis, Diseases, Extraction, Feature Extraction, Gait Analysis, Gait Classification, Image Retrieval, Industrial Electronics, Kernel Function, Kinematic Parameters, Kinematics, Learning, Linear Discriminant Analysis, Machine Learning Approaches, Motion Analysis System, Polynomial Functions, Principal Component Analysis, Support Vector Machines, SVM Classifiers}, pubstate = {published}, tppubtype = {conference} } In this research, the application of machine learning approach specifically support vector machine along with principal component analysis and linear discriminant analysis as feature extractions are evaluated and validated in discriminating gait features between normal subjects and autism children. Gait features of 32 normal and 12 autism children were recorded and analyzed using VICON motion analysis system and a force platform during normal walking. Here, twenty one gait features describing the three types of gait characteristics namely basic, kinetic and kinematic in these children are extracted. Further, with these gait features as input during classification, the ability of SVM as classifier are investigated using three different kernel functions specifically linear, polynomial, and radial basis. Results showed that LDA as feature extraction is the highest accuracy with kinematic parameters as gait features along with polynomial function as kernel for the SVM classifier. This finding proven that LDA is suitable as feature extraction and SVM is indeed apt as gait classifier in classifying the gait pattern autism and normal children. © 2016 IEEE. |
2016 |
Miskam, M A; Shamsuddin, S; Yussof, H; Ariffin, I M; Omar, A R Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781479966783, (cited By 1). Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, Autism, Autism Therapies, Behavioral Research, Children with Autism, Cognitive Interaction, Diseases, Education, Emotion, Emotion Gestures, Human Behaviours, Humanoid Robot, Humanoid Robot NAO, Robotics, Robots, Social Sciences, Surveys, Teaching, Teaching Module @conference{Miskam2016, title = {A questionnaire-based survey: Therapist's response on emotions gestures using humanoid robot for autism}, author = {M A Miskam and S Shamsuddin and H Yussof and I M Ariffin and A R Omar}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84966605834&doi=10.1109%2fMHS.2015.7438298&partnerID=40&md5=c0cbd143f24183861955c67562e36fdf}, doi = {10.1109/MHS.2015.7438298}, isbn = {9781479966783}, year = {2016}, date = {2016-01-01}, journal = {2015 International Symposium on Micro-NanoMechatronics and Human Science, MHS 2015}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {This paper is, we used a humanoid robot to physically show emotional poses and conduct a simple guessing game with children. Nine different emotions using the robot's body poses have been developed using Choregraphe. Naturally, we need to approximate as closely as possible natural human behaviour to be done by robot to engaging the children to interact with normal human. Therefore, this study is continuation of our previous study on emotion gestures where we get the therapists response towards module of emotions-based teaching module for children with autism. The role of therapists is to give their main knowledge of autism therapy to bring the right creation of module program using robot. © 2015 IEEE.}, note = {cited By 1}, keywords = {Anthropomorphic Robots, Autism, Autism Therapies, Behavioral Research, Children with Autism, Cognitive Interaction, Diseases, Education, Emotion, Emotion Gestures, Human Behaviours, Humanoid Robot, Humanoid Robot NAO, Robotics, Robots, Social Sciences, Surveys, Teaching, Teaching Module}, pubstate = {published}, tppubtype = {conference} } This paper is, we used a humanoid robot to physically show emotional poses and conduct a simple guessing game with children. Nine different emotions using the robot's body poses have been developed using Choregraphe. Naturally, we need to approximate as closely as possible natural human behaviour to be done by robot to engaging the children to interact with normal human. Therefore, this study is continuation of our previous study on emotion gestures where we get the therapists response towards module of emotions-based teaching module for children with autism. The role of therapists is to give their main knowledge of autism therapy to bring the right creation of module program using robot. © 2015 IEEE. |
Nor, M N M; Jailani, R; Tahir, N M Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781509015436, (cited By 4). Abstract | Links | BibTeX | Tags: ASD Children, Autism Spectrum Disorders, Diseases, Electromyography, Gases, Gastrocnemius, Human Motions, Industrial Electronics, Muscle, Tibialis Anterior, Typical Development, Walking Gait, Walking Pattern @conference{Nor2016226, title = {Analysis of EMG signals of TA and GAS muscles during walking of Autism Spectrum Disorder (ASD) children}, author = {M N M Nor and R Jailani and N M Tahir}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992153602&doi=10.1109%2fISCAIE.2016.7575068&partnerID=40&md5=7aaa147660a67bf4c2ddaa31f0e78717}, doi = {10.1109/ISCAIE.2016.7575068}, isbn = {9781509015436}, year = {2016}, date = {2016-01-01}, journal = {ISCAIE 2016 - 2016 IEEE Symposium on Computer Applications and Industrial Electronics}, pages = {226-230}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {This paper presents an analysis of Electromyography (EMG) signals of lower limb muscles during walking among children. Total of 18 children consists of 8 Autism Spectrum Disorder (ASD) children and 10 Typical Development (TD) children aged between 6 to 13 years old were participated in this study. The muscles of Tibialis Anterior (TA) and Gastrocnemius (GAS) were examined and the EMG signals data were obtained using Trigno Wireless EMG System at Human Motion and Analysis Laboratory, UiTM Shah Alam. The EMG signals patterns for TA and GAS muscles will be explained and the independent t-Test will be analyzed to investigate the differences of walking gait in ASD children and TD children. The result shows that there is significant differences at Gastrocnemius (GAS) muscle between ASD and TD children during midstance where p value is equal to 0.042. From this study, the EMG signal for GAS muscle play an important role in differentiate between ASD and TD children. © 2016 IEEE.}, note = {cited By 4}, keywords = {ASD Children, Autism Spectrum Disorders, Diseases, Electromyography, Gases, Gastrocnemius, Human Motions, Industrial Electronics, Muscle, Tibialis Anterior, Typical Development, Walking Gait, Walking Pattern}, pubstate = {published}, tppubtype = {conference} } This paper presents an analysis of Electromyography (EMG) signals of lower limb muscles during walking among children. Total of 18 children consists of 8 Autism Spectrum Disorder (ASD) children and 10 Typical Development (TD) children aged between 6 to 13 years old were participated in this study. The muscles of Tibialis Anterior (TA) and Gastrocnemius (GAS) were examined and the EMG signals data were obtained using Trigno Wireless EMG System at Human Motion and Analysis Laboratory, UiTM Shah Alam. The EMG signals patterns for TA and GAS muscles will be explained and the independent t-Test will be analyzed to investigate the differences of walking gait in ASD children and TD children. The result shows that there is significant differences at Gastrocnemius (GAS) muscle between ASD and TD children during midstance where p value is equal to 0.042. From this study, the EMG signal for GAS muscle play an important role in differentiate between ASD and TD children. © 2016 IEEE. |
Ilias, S; Tahir, N M; Jailani, R; Hasan, C Z C Classification of autism children gait patterns using Neural Network and Support Vector Machine Conference Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781509015436, (cited By 5). Abstract | Links | BibTeX | Tags: Accuracy Rate, Autism, Classification (of information), Diseases, Gait Analysis, Gait Parameters, Gait Pattern, Industrial Electronics, Kinematics, Neural Networks, NN Classifiers, Sensitivity and Specificity, Support Vector Machines, Three Categories @conference{Ilias201652, title = {Classification of autism children gait patterns using Neural Network and Support Vector Machine}, author = {S Ilias and N M Tahir and R Jailani and C Z C Hasan}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992135613&doi=10.1109%2fISCAIE.2016.7575036&partnerID=40&md5=55c6d166768ed5fa3b504a2bd3441829}, doi = {10.1109/ISCAIE.2016.7575036}, isbn = {9781509015436}, year = {2016}, date = {2016-01-01}, journal = {ISCAIE 2016 - 2016 IEEE Symposium on Computer Applications and Industrial Electronics}, pages = {52-56}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {In this study, we deemed further to evaluate the performance of Neural Network (NN) and Support Vector Machine (SVM) in classifying the gait patterns between autism and normal children. Firstly, temporal spatial, kinetic and kinematic gait parameters of forty four subjects namely thirty two normal subjects and twelve autism children are acquired. Next, these three category gait parameters acted as inputs to both classifiers. Results showed that fusion of temporal spatial and kinematic contributed the highest accuracy rate for NN classifier specifically 95% whilst SVM with polynomial as kernel, 95% accuracy rate is contributed by fusion of all gait parameters as inputs to the classifier. In addition, the classifiers performance is validated by computing both value of sensitivity and specificity. With SVM using polynomial as kernel, sensitivity attained is 100% indicated that the classifier's ability to perfectly discriminate normal subjects from autism subjects whilst 85% specificity showed that SVM is able to identify autism subjects as autism based on their gait patterns at 85% rate. © 2016 IEEE.}, note = {cited By 5}, keywords = {Accuracy Rate, Autism, Classification (of information), Diseases, Gait Analysis, Gait Parameters, Gait Pattern, Industrial Electronics, Kinematics, Neural Networks, NN Classifiers, Sensitivity and Specificity, Support Vector Machines, Three Categories}, pubstate = {published}, tppubtype = {conference} } In this study, we deemed further to evaluate the performance of Neural Network (NN) and Support Vector Machine (SVM) in classifying the gait patterns between autism and normal children. Firstly, temporal spatial, kinetic and kinematic gait parameters of forty four subjects namely thirty two normal subjects and twelve autism children are acquired. Next, these three category gait parameters acted as inputs to both classifiers. Results showed that fusion of temporal spatial and kinematic contributed the highest accuracy rate for NN classifier specifically 95% whilst SVM with polynomial as kernel, 95% accuracy rate is contributed by fusion of all gait parameters as inputs to the classifier. In addition, the classifiers performance is validated by computing both value of sensitivity and specificity. With SVM using polynomial as kernel, sensitivity attained is 100% indicated that the classifier's ability to perfectly discriminate normal subjects from autism subjects whilst 85% specificity showed that SVM is able to identify autism subjects as autism based on their gait patterns at 85% rate. © 2016 IEEE. |
Muty, N; Azizul, Z Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781509016365, (cited By 2). Abstract | Links | BibTeX | Tags: Arm Flapping, Autism Spectrum Disorders, Children with Autism, Computation Theory, Computational Framework, Diseases, Human Action Recognition, Human Pose Estimations, Image Recognition, Pose Estimation, Skeletal Representation @conference{Muty2016, title = {Detecting arm flapping in children with Autism Spectrum Disorder using human pose estimation and skeletal representation algorithms}, author = {N Muty and Z Azizul}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85011297898&doi=10.1109%2fICAICTA.2016.7803118&partnerID=40&md5=e11241ced18900dbe4aab19c78c1a349}, doi = {10.1109/ICAICTA.2016.7803118}, isbn = {9781509016365}, year = {2016}, date = {2016-01-01}, journal = {4th IGNITE Conference and 2016 International Conference on Advanced Informatics: Concepts, Theory and Application, ICAICTA 2016}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {Stereotypical behaviour such as arm flapping is among the prominent early signs for young children with Autism Spectrum Disorder (ASD). Diagnosis of arm flapping requires clinicians to use the standard Repetitive Behaviour Scale-Revised (RBSR) which is a structured questionnaire with the caregivers to detect the arm flapping behavioural patterns or cues. This method involves clinicians in multiple long sessions, risking a delay in diagnosis and usually an expensive process. Moreover, trained clinicians may not be available in some areas. The focus of this work is to propose a development of a computational framework to automate the diagnosis process of arm flapping. Here, we show how the human action recognition (HAR) techniques, namely, the pose estimation and the skeletal representation are utilized simultaneously to segment parts of the human body (head, neck, elbows and shoulders) into stickman model. We show how the stickman model allows us to estimate arm asymmetry (during arm flapping) which indicates possible sign of autism. The framework developed has been tested against data taken from a public database and has shown a high accuracy in detecting the repetitive behavioural pattern among young children. The results show that our method can provide efficient results in clinical assessment. © 2016 IEEE.}, note = {cited By 2}, keywords = {Arm Flapping, Autism Spectrum Disorders, Children with Autism, Computation Theory, Computational Framework, Diseases, Human Action Recognition, Human Pose Estimations, Image Recognition, Pose Estimation, Skeletal Representation}, pubstate = {published}, tppubtype = {conference} } Stereotypical behaviour such as arm flapping is among the prominent early signs for young children with Autism Spectrum Disorder (ASD). Diagnosis of arm flapping requires clinicians to use the standard Repetitive Behaviour Scale-Revised (RBSR) which is a structured questionnaire with the caregivers to detect the arm flapping behavioural patterns or cues. This method involves clinicians in multiple long sessions, risking a delay in diagnosis and usually an expensive process. Moreover, trained clinicians may not be available in some areas. The focus of this work is to propose a development of a computational framework to automate the diagnosis process of arm flapping. Here, we show how the human action recognition (HAR) techniques, namely, the pose estimation and the skeletal representation are utilized simultaneously to segment parts of the human body (head, neck, elbows and shoulders) into stickman model. We show how the stickman model allows us to estimate arm asymmetry (during arm flapping) which indicates possible sign of autism. The framework developed has been tested against data taken from a public database and has shown a high accuracy in detecting the repetitive behavioural pattern among young children. The results show that our method can provide efficient results in clinical assessment. © 2016 IEEE. |
Aziz, N S A; Ahmad, W F W; Hashim, A S Development phase of mobile numerical application for children with autism: Math4Autism Conference Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781509051342, (cited By 1). Abstract | Links | BibTeX | Tags: Autism, Children with Autism, Computer Aided Instruction, Development Phase, Diseases, E-learning, Information and Communications Technology, Information Science, Learning, Life Cycle, Mobile Applications, Mobile Devices, Mobile Learning, Numerical Applications, Software Prototyping, Teaching @conference{Aziz2016542, title = {Development phase of mobile numerical application for children with autism: Math4Autism}, author = {N S A Aziz and W F W Ahmad and A S Hashim}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010461776&doi=10.1109%2fICCOINS.2016.7783273&partnerID=40&md5=092bea803c38715887a236f5a14af3d9}, doi = {10.1109/ICCOINS.2016.7783273}, isbn = {9781509051342}, year = {2016}, date = {2016-01-01}, journal = {2016 3rd International Conference on Computer and Information Sciences, ICCOINS 2016 - Proceedings}, pages = {542-546}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {The use of mobile devices in teaching and learning has intensified in this era of information and communication technology. The utilization of mobile learning application created learning beyond the boundaries of four wall of the traditional classrooms. The mobile learning application can be used everywhere at any time. This fits the restraint of the children with autism. The development lifecycle used to develop the working prototype, was adapted from ADDIE lifecycle which consists of five phases; analysis, design, development, implementation and evaluation. This paper objectively presents the development phase of the Math4Autism development lifecycle. Math4Autism is a prototype of mobile learning application developed for the children with Autism to learn basic numbers, basic shapes and sizes. This paper discusses the tools used in developing the working prototype and presents the menu hierarchy for the prototype. The working prototype was tested to ensure its functionality works and free from errors. The result shows that the working prototype is ready to be tested to the real users. © 2016 IEEE.}, note = {cited By 1}, keywords = {Autism, Children with Autism, Computer Aided Instruction, Development Phase, Diseases, E-learning, Information and Communications Technology, Information Science, Learning, Life Cycle, Mobile Applications, Mobile Devices, Mobile Learning, Numerical Applications, Software Prototyping, Teaching}, pubstate = {published}, tppubtype = {conference} } The use of mobile devices in teaching and learning has intensified in this era of information and communication technology. The utilization of mobile learning application created learning beyond the boundaries of four wall of the traditional classrooms. The mobile learning application can be used everywhere at any time. This fits the restraint of the children with autism. The development lifecycle used to develop the working prototype, was adapted from ADDIE lifecycle which consists of five phases; analysis, design, development, implementation and evaluation. This paper objectively presents the development phase of the Math4Autism development lifecycle. Math4Autism is a prototype of mobile learning application developed for the children with Autism to learn basic numbers, basic shapes and sizes. This paper discusses the tools used in developing the working prototype and presents the menu hierarchy for the prototype. The working prototype was tested to ensure its functionality works and free from errors. The result shows that the working prototype is ready to be tested to the real users. © 2016 IEEE. |
2015 |
Shamsuddin, S; Yussof, H; Hanapiah, F A; Mohamed, S A content validated tool to observe autism behavior in child-robot interaction Conference 2015-November , Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781467367042, (cited By 1). Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, Autistic Children, Child-Robot Interactions, Children with Autism, Cronbach's Alphas, Diseases, Humanoid Robot, Internal Consistency, Mental Disorders, Robotics, Robots, Validation Study @conference{Shamsuddin201543, title = {A content validated tool to observe autism behavior in child-robot interaction}, author = {S Shamsuddin and H Yussof and F A Hanapiah and S Mohamed}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84954049574&doi=10.1109%2fROMAN.2015.7333578&partnerID=40&md5=2a25d12804ba227de6f26eca7b46f770}, doi = {10.1109/ROMAN.2015.7333578}, isbn = {9781467367042}, year = {2015}, date = {2015-01-01}, journal = {Proceedings - IEEE International Workshop on Robot and Human Interactive Communication}, volume = {2015-November}, pages = {43-47}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {This research presents the validation study of a qualitative tool to analyze the response in robot-based intervention. The 24 behavioral items in the tool were determined through routine observations carried out by clinicians and the definitions of autism adopted by the Diagnostic and Statistical Manual of Mental Disorders: Fourth Edition-Text Revision (DSM-IV-TR). 34 experts determined content validity and tool reliability by viewpoints through the Likert scale. The tool was found to have good content validity with more than 67% of experts scored at least 3 on the 5-point Likert scale. Cronbach's alpha coefficient of 0.872 reflected the tool's content reliability and internal consistency. The tool was used to analyze the behavior response of children with autism when exposed to a humanoid robot. It functioned as a score-sheet to compare the behavior of autistic children with and without the presence of a robot. These findings put forward a tool with contents considered valid to evaluate behavior outcome of studies involving children with autism and robots. © 2015 IEEE.}, note = {cited By 1}, keywords = {Anthropomorphic Robots, Autistic Children, Child-Robot Interactions, Children with Autism, Cronbach's Alphas, Diseases, Humanoid Robot, Internal Consistency, Mental Disorders, Robotics, Robots, Validation Study}, pubstate = {published}, tppubtype = {conference} } This research presents the validation study of a qualitative tool to analyze the response in robot-based intervention. The 24 behavioral items in the tool were determined through routine observations carried out by clinicians and the definitions of autism adopted by the Diagnostic and Statistical Manual of Mental Disorders: Fourth Edition-Text Revision (DSM-IV-TR). 34 experts determined content validity and tool reliability by viewpoints through the Likert scale. The tool was found to have good content validity with more than 67% of experts scored at least 3 on the 5-point Likert scale. Cronbach's alpha coefficient of 0.872 reflected the tool's content reliability and internal consistency. The tool was used to analyze the behavior response of children with autism when exposed to a humanoid robot. It functioned as a score-sheet to compare the behavior of autistic children with and without the presence of a robot. These findings put forward a tool with contents considered valid to evaluate behavior outcome of studies involving children with autism and robots. © 2015 IEEE. |
Sitimin, S A; Ismail, Z; Fikry, A; Hassan, H; Ahmad, S S; Samat, N; Musa, R; Hashim, R A review on employee benefits for working parents with autistic children Conference Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479957651, (cited By 1). Abstract | Links | BibTeX | Tags: Autism, Autistic Children, Children with Autism, Communication Skills, Developed Countries, Diseases, Employee Benefits, Manufacture, Robotics, Social Interactions, Working Parents @conference{Sitimin2015176, title = {A review on employee benefits for working parents with autistic children}, author = {S A Sitimin and Z Ismail and A Fikry and H Hassan and S S Ahmad and N Samat and R Musa and R Hashim}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959565959&doi=10.1109%2fROMA.2014.7295883&partnerID=40&md5=30b39811730957e0eb810658605e007a}, doi = {10.1109/ROMA.2014.7295883}, isbn = {9781479957651}, year = {2015}, date = {2015-01-01}, journal = {2014 IEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014}, pages = {176-179}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {Autism is a behavioural illness categorized based on poor communication skills, lack of social interaction and weird way of playing. As a caregiver and a worker at the same time, 78 per cent of employees sometimes had to take short time off or leave early from work, come to work late, and being absence for a long period of time. Since children with autism needs more health services and attention, working parents are hoping to get better employees benefits from their employers. Mostly, in developed countries such as United States, employee benefits for working parents with autistic children is applicable but the employees benefits provided are very limited and it is based on the organization's benefit policies. This research provides a general review on previous related studies especially the one which is closely related to employee benefits for working parents with autistic children. Thus, this research can contribute to the new knowledge in creating special employee benefits in the workplace for working parents with autistic children globally. © 2014 IEEE.}, note = {cited By 1}, keywords = {Autism, Autistic Children, Children with Autism, Communication Skills, Developed Countries, Diseases, Employee Benefits, Manufacture, Robotics, Social Interactions, Working Parents}, pubstate = {published}, tppubtype = {conference} } Autism is a behavioural illness categorized based on poor communication skills, lack of social interaction and weird way of playing. As a caregiver and a worker at the same time, 78 per cent of employees sometimes had to take short time off or leave early from work, come to work late, and being absence for a long period of time. Since children with autism needs more health services and attention, working parents are hoping to get better employees benefits from their employers. Mostly, in developed countries such as United States, employee benefits for working parents with autistic children is applicable but the employees benefits provided are very limited and it is based on the organization's benefit policies. This research provides a general review on previous related studies especially the one which is closely related to employee benefits for working parents with autistic children. Thus, this research can contribute to the new knowledge in creating special employee benefits in the workplace for working parents with autistic children globally. © 2014 IEEE. |
Yussof, H; Salleh, M H; Miskam, M A; Shamsuddin, S; Omar, A R ASKNAO apps targeting at social skills development for children with autism Conference 2015-October , IEEE Computer Society, 2015, ISSN: 21618070, (cited By 3). Abstract | Links | BibTeX | Tags: Automation, Children with Autism, Communication Skills, Diseases, Education, Social Skills @conference{Yussof2015973, title = {ASKNAO apps targeting at social skills development for children with autism}, author = {H Yussof and M H Salleh and M A Miskam and S Shamsuddin and A R Omar}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84952770737&doi=10.1109%2fCoASE.2015.7294225&partnerID=40&md5=bb2d8f8a5d54a457dec4137e1a55514a}, doi = {10.1109/CoASE.2015.7294225}, issn = {21618070}, year = {2015}, date = {2015-01-01}, journal = {IEEE International Conference on Automation Science and Engineering}, volume = {2015-October}, pages = {973-978}, publisher = {IEEE Computer Society}, abstract = {This paper aims to review the ASKNAO apps targeting at social skills of children with autism. The ASKNAO Apps is a system that designed to teach children with autism the basic skills that are naturally learned by the typical children. Since ASKNAO apps is a commercial based system, the contents are yet to be categorized technically and specifically in accordance to the three autism criteria which are social skills, communication skills and repetitive behavior. By taking the first step in identifying the Apps suitability focusing on social skills, further study on application and assessment of ASKNAO can be conducted to teach the child in the direction of the user's requirements. © 2015 IEEE.}, note = {cited By 3}, keywords = {Automation, Children with Autism, Communication Skills, Diseases, Education, Social Skills}, pubstate = {published}, tppubtype = {conference} } This paper aims to review the ASKNAO apps targeting at social skills of children with autism. The ASKNAO Apps is a system that designed to teach children with autism the basic skills that are naturally learned by the typical children. Since ASKNAO apps is a commercial based system, the contents are yet to be categorized technically and specifically in accordance to the three autism criteria which are social skills, communication skills and repetitive behavior. By taking the first step in identifying the Apps suitability focusing on social skills, further study on application and assessment of ASKNAO can be conducted to teach the child in the direction of the user's requirements. © 2015 IEEE. |
Saleh, N M; Hassan, H; Fikry, A; Musa, R; Ahmad, S S; Ismail, Z; Samat, N; Hashim, R Autism children: Cost and benefit analysis of using humanoid in Malaysia Conference Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479957651, (cited By 3). Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, Autism, Autism Therapies, Autism Treatments, Children, Cost Benefit Analysis, Costs, Curing, Diseases, Humanoid, Humanoid Robot, Manufacture, Quality of Life, Robotics, Robots @conference{Saleh2015185, title = {Autism children: Cost and benefit analysis of using humanoid in Malaysia}, author = {N M Saleh and H Hassan and A Fikry and R Musa and S S Ahmad and Z Ismail and N Samat and R Hashim}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959570138&doi=10.1109%2fROMA.2014.7295885&partnerID=40&md5=e3a60d8df8ebd4f38287d5f212c8ab1a}, doi = {10.1109/ROMA.2014.7295885}, isbn = {9781479957651}, year = {2015}, date = {2015-01-01}, journal = {2014 IEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014}, pages = {185-187}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {Autism is a permanent disorder that cause quality of life disturbance. As matter of research, there are no single interventions that can cure the heterogeneous syndrome. Since there is no cure for autism children, perhaps using humanoid can help the autism children in order to have appropriate therapy and treatment programs especially to the young children inflicted with it. Robots are normally used for industrial work, but hardly for therapy. Robots have been used to substitute human way back in the 19th century. They are beneficial to society regardless of the fields that they are being utilized. The health sector has been identified as one of the fields that benefit most as a result of using robotics. For decades, people fascinated with the technology's fiction of robots that look and act like a human Therefore, humanoid robots give benefits towards autism therapy for early detection. Many studies have been done in order to determine the ways to conduct autism treatment However, there is no study on cost and benefit analysis conducted using humanoid as a treatment for autism children. Therefore, this study will focus on the cost and benefit analysis of using humanoid for Malaysian autism children. © 2014 IEEE.}, note = {cited By 3}, keywords = {Anthropomorphic Robots, Autism, Autism Therapies, Autism Treatments, Children, Cost Benefit Analysis, Costs, Curing, Diseases, Humanoid, Humanoid Robot, Manufacture, Quality of Life, Robotics, Robots}, pubstate = {published}, tppubtype = {conference} } Autism is a permanent disorder that cause quality of life disturbance. As matter of research, there are no single interventions that can cure the heterogeneous syndrome. Since there is no cure for autism children, perhaps using humanoid can help the autism children in order to have appropriate therapy and treatment programs especially to the young children inflicted with it. Robots are normally used for industrial work, but hardly for therapy. Robots have been used to substitute human way back in the 19th century. They are beneficial to society regardless of the fields that they are being utilized. The health sector has been identified as one of the fields that benefit most as a result of using robotics. For decades, people fascinated with the technology's fiction of robots that look and act like a human Therefore, humanoid robots give benefits towards autism therapy for early detection. Many studies have been done in order to determine the ways to conduct autism treatment However, there is no study on cost and benefit analysis conducted using humanoid as a treatment for autism children. Therefore, this study will focus on the cost and benefit analysis of using humanoid for Malaysian autism children. © 2014 IEEE. |
Isa, N R M; Yusoff, M; Khalid, N E; Tahir, N; Nikmat, Binti A W Autism severity level detection using fuzzy expert system Conference Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479957651, (cited By 2). Abstract | Links | BibTeX | Tags: Autism, Autism Severity Level, Autistic Children, Children with Autism, Data Acquisition, Developmental Disorders, Diseases, Education, Expert Systems, Fuzzy Expert Systems, Level Detections, Manufacture, Robotics, Social Communications, Surveys, System Architectures, Teaching @conference{Isa2015218, title = {Autism severity level detection using fuzzy expert system}, author = {N R M Isa and M Yusoff and N E Khalid and N Tahir and A W Binti Nikmat}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959503922&doi=10.1109%2fROMA.2014.7295891&partnerID=40&md5=63e742d59b785d14f87d98dac7dd71ee}, doi = {10.1109/ROMA.2014.7295891}, isbn = {9781479957651}, year = {2015}, date = {2015-01-01}, journal = {2014 IEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014}, pages = {218-223}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {Autism is a neuro developmental disorder that is recently well known among Malaysian. Many researches on autism detection have been conducted worldwide. However, there is lack of research conducted in detecting autism severity level. Therefore, this paper focuses on autism severity level detection using fuzzy expert system. Two main autistic behavioral criteria are selected which are social communication impairment and restricted repetitive behavior. Data acquisition was based on interview sessions with clinical psychologist and distribution of 36 questionnaires to teachers and parents that have autistic children. It was then analyzed and the cut off points for each severity level; level 1 (mild), level 2 (moderate), and level 3 (severe) is determined. The fuzzy expert system processes are employed to detect the severity levels. The processes involve Fuzzy system architecture, fuzzification, rules evaluation, rules evaluation and defuzzification. The finding demonstrates that the system is able to detect autism severity level with a good accuracy. This system also accommodates with suitable recommendation based on the generated result whether the suggestion is to go for speech therapy or behavior therapy. © 2014 IEEE.}, note = {cited By 2}, keywords = {Autism, Autism Severity Level, Autistic Children, Children with Autism, Data Acquisition, Developmental Disorders, Diseases, Education, Expert Systems, Fuzzy Expert Systems, Level Detections, Manufacture, Robotics, Social Communications, Surveys, System Architectures, Teaching}, pubstate = {published}, tppubtype = {conference} } Autism is a neuro developmental disorder that is recently well known among Malaysian. Many researches on autism detection have been conducted worldwide. However, there is lack of research conducted in detecting autism severity level. Therefore, this paper focuses on autism severity level detection using fuzzy expert system. Two main autistic behavioral criteria are selected which are social communication impairment and restricted repetitive behavior. Data acquisition was based on interview sessions with clinical psychologist and distribution of 36 questionnaires to teachers and parents that have autistic children. It was then analyzed and the cut off points for each severity level; level 1 (mild), level 2 (moderate), and level 3 (severe) is determined. The fuzzy expert system processes are employed to detect the severity levels. The processes involve Fuzzy system architecture, fuzzification, rules evaluation, rules evaluation and defuzzification. The finding demonstrates that the system is able to detect autism severity level with a good accuracy. This system also accommodates with suitable recommendation based on the generated result whether the suggestion is to go for speech therapy or behavior therapy. © 2014 IEEE. |
Rahim, M H B A; Zamin, N AUTISTHERAPIBOT: Autonomous robotic autism therapists assistant for autistic children Conference Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479957651, (cited By 1). Abstract | Links | BibTeX | Tags: Asperger Syndrome, Assistant Robot, Autism Spectrum Disorders, Autonomous Robotics, Diseases, Learning, Manufacture, Process of Learning, Robotics, Robots, Traditional Learning @conference{Rahim2015248, title = {AUTISTHERAPIBOT: Autonomous robotic autism therapists assistant for autistic children}, author = {M H B A Rahim and N Zamin}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959477969&doi=10.1109%2fROMA.2014.7295896&partnerID=40&md5=97aba13712e291d19218c277f557e204}, doi = {10.1109/ROMA.2014.7295896}, isbn = {9781479957651}, year = {2015}, date = {2015-01-01}, journal = {2014 IEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014}, pages = {248-253}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {Recent studies unravels that Autistic Spectrum Disorder which include Asperger Syndrome have many bad impacts. Among the symptoms of ASD are difficulties to focus that leads to difficulties in learning especially to those ASD children. Thus, the objective of this project is to investigate the current teaching method used by the autism therapists and solve the weaknesses via robotic means. The NXT will be used in order to aid the therapists in educating those children with ASD. Upon the completion of the prototype, it will be tested against the autistic children to check on the efficacy of the developed prototype. The project will focus on how to attract the autistic children into learning via the usage of robotic application. In a preliminary investigation, multiple robotic designs and programming approach are studied to produce a robotic application that can assist therapists and engage with the target autistic children in order to facilitate their process of learning. Interviews with the therapists and live observation at the selected special school are conducted to understand the traditional learning process that are used by the therapists and identify the weaknesses in it to improvise it. The significance of this robotic application is to fulfill the depravedness in the learning capabilities of the autistic children and also to assist the therapists in their daily routine. © 2014 IEEE.}, note = {cited By 1}, keywords = {Asperger Syndrome, Assistant Robot, Autism Spectrum Disorders, Autonomous Robotics, Diseases, Learning, Manufacture, Process of Learning, Robotics, Robots, Traditional Learning}, pubstate = {published}, tppubtype = {conference} } Recent studies unravels that Autistic Spectrum Disorder which include Asperger Syndrome have many bad impacts. Among the symptoms of ASD are difficulties to focus that leads to difficulties in learning especially to those ASD children. Thus, the objective of this project is to investigate the current teaching method used by the autism therapists and solve the weaknesses via robotic means. The NXT will be used in order to aid the therapists in educating those children with ASD. Upon the completion of the prototype, it will be tested against the autistic children to check on the efficacy of the developed prototype. The project will focus on how to attract the autistic children into learning via the usage of robotic application. In a preliminary investigation, multiple robotic designs and programming approach are studied to produce a robotic application that can assist therapists and engage with the target autistic children in order to facilitate their process of learning. Interviews with the therapists and live observation at the selected special school are conducted to understand the traditional learning process that are used by the therapists and identify the weaknesses in it to improvise it. The significance of this robotic application is to fulfill the depravedness in the learning capabilities of the autistic children and also to assist the therapists in their daily routine. © 2014 IEEE. |
Aziz, A A; Moganan, F F M; Ismail, A; Lokman, A M Autistic Children's Kansei Responses Towards Humanoid-Robot as Teaching Mediator Conference 76 , Elsevier B.V., 2015, ISSN: 18770509, (cited By 6). Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, Autism Spectrum Disorders, Children with Autism, Diseases, Education, Emotion, Emotion Extractions, Humanoid Robot, Humanoid Robot NAO, Intelligent Control, Interaction Modules, Kansei Engineering, Robotics, Robots, Smart Sensors, Social Communications @conference{Aziz2015488, title = {Autistic Children's Kansei Responses Towards Humanoid-Robot as Teaching Mediator}, author = {A A Aziz and F F M Moganan and A Ismail and A M Lokman}, editor = {Miskon M F Yussof H.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962865419&doi=10.1016%2fj.procs.2015.12.322&partnerID=40&md5=2406a6eb6d803f72684751a8aab37868}, doi = {10.1016/j.procs.2015.12.322}, issn = {18770509}, year = {2015}, date = {2015-01-01}, journal = {Procedia Computer Science}, volume = {76}, pages = {488-493}, publisher = {Elsevier B.V.}, abstract = {Autism is often being associated with the deficits in social communication, interaction as well as imagination. Autistic patients may experience the impairment in social interaction usually being related to their inability to interpret others' emotion and even to express their own feelings. As a result, children with autism are often been labeled as lacking the ability to express their emotion. The main objective of this paper is to present a pilot study in studying the autistic children's' emotions and feelings upon being triggered by the humanoid-robot, NAO. Kansei Engineering, which is a powerful emotion extraction mechanism is adopted in the study to assess the children's' emotion. The experiment involved two autistic children and one normal child who were given four interaction modules in separate intervention session. The experiment conducted is to observe how robot triggers the emotion of these children. The result shows that different types of modules which would trigger different emotional reactions. This result provides a basis for further investigation of the assessment of autistic children's feeling and emotion. The result will ultimately contribute to finding best possible therapy for autistic children towards the used of humanoid-robot.}, note = {cited By 6}, keywords = {Anthropomorphic Robots, Autism Spectrum Disorders, Children with Autism, Diseases, Education, Emotion, Emotion Extractions, Humanoid Robot, Humanoid Robot NAO, Intelligent Control, Interaction Modules, Kansei Engineering, Robotics, Robots, Smart Sensors, Social Communications}, pubstate = {published}, tppubtype = {conference} } Autism is often being associated with the deficits in social communication, interaction as well as imagination. Autistic patients may experience the impairment in social interaction usually being related to their inability to interpret others' emotion and even to express their own feelings. As a result, children with autism are often been labeled as lacking the ability to express their emotion. The main objective of this paper is to present a pilot study in studying the autistic children's' emotions and feelings upon being triggered by the humanoid-robot, NAO. Kansei Engineering, which is a powerful emotion extraction mechanism is adopted in the study to assess the children's' emotion. The experiment involved two autistic children and one normal child who were given four interaction modules in separate intervention session. The experiment conducted is to observe how robot triggers the emotion of these children. The result shows that different types of modules which would trigger different emotional reactions. This result provides a basis for further investigation of the assessment of autistic children's feeling and emotion. The result will ultimately contribute to finding best possible therapy for autistic children towards the used of humanoid-robot. |
Khir, N H B M; Ismail, M; Jamil, N; Razak, F H A Can spatiotemporal gait analysis identify a child with Autistic Spectrum Disorder? Conference Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479957651, (cited By 0). Abstract | Links | BibTeX | Tags: Autism, Autism Spectrum Disorders, Children with Autism, Critical Analysis, Diseases, Economic and Social Effects, Gait Analysis, Gait Pattern, Literature Reviews, Manufacture, Quantitative Study, Robotics, Spatiotemporal @conference{Khir2015115, title = {Can spatiotemporal gait analysis identify a child with Autistic Spectrum Disorder?}, author = {N H B M Khir and M Ismail and N Jamil and F H A Razak}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959505294&doi=10.1109%2fROMA.2014.7295872&partnerID=40&md5=dbaae7a86b78fa037d60f4b944ed2dc6}, doi = {10.1109/ROMA.2014.7295872}, isbn = {9781479957651}, year = {2015}, date = {2015-01-01}, journal = {2014 IEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014}, pages = {115-119}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {The aim of this study is to investigate the ability of spatiotemporal gait analysis to identify the Autistic Spectrum Disorder child (ASD). Even though the interest in gait analysis is becoming popular among researchers these days, yet very few quantitative studies are done on children with autism. Since motor development is not influenced by both social and linguistic development, it is believed to be a probable bio-marker of autism. The spatiotemporal gait pattern is being explored to understand the difference it may bring upon in the future. Six findings from previous researches are reviewed and analyzed to understand the crucial factor involves in this research. From the literature review and critical analysis done, spatiotemporal gait analysis may be used to identify the ASD child because the gait patterns of ASD child are discovered to be different from normal children. © 2014 IEEE.}, note = {cited By 0}, keywords = {Autism, Autism Spectrum Disorders, Children with Autism, Critical Analysis, Diseases, Economic and Social Effects, Gait Analysis, Gait Pattern, Literature Reviews, Manufacture, Quantitative Study, Robotics, Spatiotemporal}, pubstate = {published}, tppubtype = {conference} } The aim of this study is to investigate the ability of spatiotemporal gait analysis to identify the Autistic Spectrum Disorder child (ASD). Even though the interest in gait analysis is becoming popular among researchers these days, yet very few quantitative studies are done on children with autism. Since motor development is not influenced by both social and linguistic development, it is believed to be a probable bio-marker of autism. The spatiotemporal gait pattern is being explored to understand the difference it may bring upon in the future. Six findings from previous researches are reviewed and analyzed to understand the crucial factor involves in this research. From the literature review and critical analysis done, spatiotemporal gait analysis may be used to identify the ASD child because the gait patterns of ASD child are discovered to be different from normal children. © 2014 IEEE. |
Kamaruzaman, N N; Jomhari, N Digital Game-Based Learning for Low Functioning Autism Children in Learning Al-Quran Conference Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479928231, (cited By 4). Abstract | Links | BibTeX | Tags: Al-Quran, Best Model, Digital Game-Based Learning, Diseases, E-learning, Education, Education Computing, Learning, Low-Functioning Autism, Process of Learning, Serious Games @conference{Kamaruzaman2015184, title = {Digital Game-Based Learning for Low Functioning Autism Children in Learning Al-Quran}, author = {N N Kamaruzaman and N Jomhari}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84964950093&doi=10.1109%2fNOORIC.2013.46&partnerID=40&md5=f7d5517e2d29058cb7b6e571fb0191f3}, doi = {10.1109/NOORIC.2013.46}, isbn = {9781479928231}, year = {2015}, date = {2015-01-01}, journal = {Proceedings - 2013 Taibah University International Conference on Advances in Information Technology for the Holy Quran and Its Sciences, NOORIC 2013}, pages = {184-189}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {The objective of the study is to propose several prototypes of digital game-based learning (DGBL) for the education of low functioning autism (LFA) children specifically in learning Al-Quran. Study on several models of the serious game has been conducted and the best model was selected to be applied in designing the prototypes. Experiment on fifteen LFA children, age within five to ten years old will be conducted in order to evaluate the effectiveness of the game in helping the process of learning Al-Quran. The evaluation will emphasize on the usability element on its user. The expectation of this study is that the game could engage the LFA children during the learning process and make them active in learning Al-Quran. Therefore with the creation of the game, it is hoped that it will provide the LFA children with opportunities to study Al-Quran like other normal Muslim children. © 2015 IEEE.}, note = {cited By 4}, keywords = {Al-Quran, Best Model, Digital Game-Based Learning, Diseases, E-learning, Education, Education Computing, Learning, Low-Functioning Autism, Process of Learning, Serious Games}, pubstate = {published}, tppubtype = {conference} } The objective of the study is to propose several prototypes of digital game-based learning (DGBL) for the education of low functioning autism (LFA) children specifically in learning Al-Quran. Study on several models of the serious game has been conducted and the best model was selected to be applied in designing the prototypes. Experiment on fifteen LFA children, age within five to ten years old will be conducted in order to evaluate the effectiveness of the game in helping the process of learning Al-Quran. The evaluation will emphasize on the usability element on its user. The expectation of this study is that the game could engage the LFA children during the learning process and make them active in learning Al-Quran. Therefore with the creation of the game, it is hoped that it will provide the LFA children with opportunities to study Al-Quran like other normal Muslim children. © 2015 IEEE. |
Khosrowabadi, R; Quek, C; Ang, K K; Wahab, A; Chen, Annabel S -H Dynamic screening of autistic children in various mental states using pattern of connectivity between brain regions Journal Article Applied Soft Computing Journal, 32 , pp. 335-346, 2015, ISSN: 15684946, (cited By 6). Abstract | Links | BibTeX | Tags: Autism Spectrum Disorders, Biomedical Signal Processing, Brain, Connectivity Feature, Connectivity Pattern, Diseases, Electroencephalography, Face Perceptions, Feature Extraction, Functional Connectivity, Pattern Recognition, Pattern Recognition Techniques @article{Khosrowabadi2015335, title = {Dynamic screening of autistic children in various mental states using pattern of connectivity between brain regions}, author = {R Khosrowabadi and C Quek and K K Ang and A Wahab and S -H Annabel Chen}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84927922520&doi=10.1016%2fj.asoc.2015.03.030&partnerID=40&md5=5973f80db5649e5c61e344907819a18b}, doi = {10.1016/j.asoc.2015.03.030}, issn = {15684946}, year = {2015}, date = {2015-01-01}, journal = {Applied Soft Computing Journal}, volume = {32}, pages = {335-346}, publisher = {Elsevier Ltd}, abstract = {In this study, a dynamic screening strategy is proposed to discriminate subjects with autistic spectrum disorder (ASD) from healthy controls. The ASD is defined as a neurodevelopmental disorder that disrupts normal patterns of connectivity between the brain regions. Therefore, the potential use of such abnormality for autism screening is investigated. The connectivity patterns are estimated from electroencephalogram (EEG) data collected from 8 brain regions under various mental states. The EEG data of 12 healthy controls and 6 autistic children (age matched in 7-10) were collected during eyes-open and eyes-close resting states as well as when subjects were exposed to affective faces (happy, sad and calm). Subsequently, the subjects were classified as autistic or healthy groups based on their brain connectivity patterns using pattern recognition techniques. Performance of the proposed system in each mental state is separately evaluated. The results present higher recognition rates using functional connectivity features when compared against other existing feature extraction methods. © 2015 Published by Elsevier B.V.}, note = {cited By 6}, keywords = {Autism Spectrum Disorders, Biomedical Signal Processing, Brain, Connectivity Feature, Connectivity Pattern, Diseases, Electroencephalography, Face Perceptions, Feature Extraction, Functional Connectivity, Pattern Recognition, Pattern Recognition Techniques}, pubstate = {published}, tppubtype = {article} } In this study, a dynamic screening strategy is proposed to discriminate subjects with autistic spectrum disorder (ASD) from healthy controls. The ASD is defined as a neurodevelopmental disorder that disrupts normal patterns of connectivity between the brain regions. Therefore, the potential use of such abnormality for autism screening is investigated. The connectivity patterns are estimated from electroencephalogram (EEG) data collected from 8 brain regions under various mental states. The EEG data of 12 healthy controls and 6 autistic children (age matched in 7-10) were collected during eyes-open and eyes-close resting states as well as when subjects were exposed to affective faces (happy, sad and calm). Subsequently, the subjects were classified as autistic or healthy groups based on their brain connectivity patterns using pattern recognition techniques. Performance of the proposed system in each mental state is separately evaluated. The results present higher recognition rates using functional connectivity features when compared against other existing feature extraction methods. © 2015 Published by Elsevier B.V. |
Salleh, M H K; Yussof, H; Ainuddin, H A; Muda, M Z; Shamsuddin, S; Miskam, M A; Omar, A R Experimental Framework for the Categorization of Special Education Programs of ASKNAO Conference 76 , Elsevier B.V., 2015, ISSN: 18770509, (cited By 4). Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, ASKNAO, Autism, Diseases, Education, Humanoid Robot, Humanoid Robot NAO, Intelligent Control, Rehabilitation Robotics, Robotics, Smart Sensors, Special Education @conference{Salleh2015480, title = {Experimental Framework for the Categorization of Special Education Programs of ASKNAO}, author = {M H K Salleh and H Yussof and H A Ainuddin and M Z Muda and S Shamsuddin and M A Miskam and A R Omar}, editor = {Miskon M F Yussof H.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962839161&doi=10.1016%2fj.procs.2015.12.321&partnerID=40&md5=b1ef50969d7f20b587f124ebebc3a9bc}, doi = {10.1016/j.procs.2015.12.321}, issn = {18770509}, year = {2015}, date = {2015-01-01}, journal = {Procedia Computer Science}, volume = {76}, pages = {480-487}, publisher = {Elsevier B.V.}, abstract = {This paper presents the methods for categorizing a special education apps known as Autism Solution for Kids using NAO (ASKNAO) into the three subscales of autism which is Communication, Social Skills and Repetitive Behavior. The ASKNAO programs contains special education apps that is aimed for autism rehabilitation. As the apps have yet to be categorized, an experimental framework is proposed as to create a method of organizing the apps. With the usage of a 24 behavioral score sheet based on GARS-2, the reactions of the autistic children when interacting with the NAO robot during the experimental sessions can help classify the apps accordingly. There is however a few criteria needs to be met for the experimental data can be considered as reliable.}, note = {cited By 4}, keywords = {Anthropomorphic Robots, ASKNAO, Autism, Diseases, Education, Humanoid Robot, Humanoid Robot NAO, Intelligent Control, Rehabilitation Robotics, Robotics, Smart Sensors, Special Education}, pubstate = {published}, tppubtype = {conference} } This paper presents the methods for categorizing a special education apps known as Autism Solution for Kids using NAO (ASKNAO) into the three subscales of autism which is Communication, Social Skills and Repetitive Behavior. The ASKNAO programs contains special education apps that is aimed for autism rehabilitation. As the apps have yet to be categorized, an experimental framework is proposed as to create a method of organizing the apps. With the usage of a 24 behavioral score sheet based on GARS-2, the reactions of the autistic children when interacting with the NAO robot during the experimental sessions can help classify the apps accordingly. There is however a few criteria needs to be met for the experimental data can be considered as reliable. |
Moktar, M N; Fikry, A; Musa, R; Hassan, H; Ahmad, S S; Ismail, Z; Samat, N; Hashim, R Extending cultural model of assistive technology design for autism treatment Conference Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479957651, (cited By 1). Abstract | Links | BibTeX | Tags: Assistive Technology, Autism, Autism Treatments, Cell Culture, Cultural Aspects, Cultural Changes, Cultural Difference, Cultural Diversity, Design, Diseases, Manufacture, Robotics, Technological Growth @conference{Moktar2015172, title = {Extending cultural model of assistive technology design for autism treatment}, author = {M N Moktar and A Fikry and R Musa and H Hassan and S S Ahmad and Z Ismail and N Samat and R Hashim}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959542249&doi=10.1109%2fROMA.2014.7295882&partnerID=40&md5=43f3d322ae7e765e39205c5990862b05}, doi = {10.1109/ROMA.2014.7295882}, isbn = {9781479957651}, year = {2015}, date = {2015-01-01}, journal = {2014 IEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014}, pages = {172-175}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {This paper depicts the prominence of cultural on the adoption of assistive technology, in terms of design, which are particularly anticipated for autism treatment. The researchers believe that cultural aspect should be considered in designing assistive technology in treating autistic individual. It is necessary to assess cultural differences critically so that assistive technology can be accepted extensively. Occasional review on cultural changes is also needed in countries with cultural diversity to ensure that the technological growth is compatible with the current recognition. This paper reviews on disability treatment using assistive technology and proposes an extension for the existing cultural model for assistive technology design. © 2014 IEEE.}, note = {cited By 1}, keywords = {Assistive Technology, Autism, Autism Treatments, Cell Culture, Cultural Aspects, Cultural Changes, Cultural Difference, Cultural Diversity, Design, Diseases, Manufacture, Robotics, Technological Growth}, pubstate = {published}, tppubtype = {conference} } This paper depicts the prominence of cultural on the adoption of assistive technology, in terms of design, which are particularly anticipated for autism treatment. The researchers believe that cultural aspect should be considered in designing assistive technology in treating autistic individual. It is necessary to assess cultural differences critically so that assistive technology can be accepted extensively. Occasional review on cultural changes is also needed in countries with cultural diversity to ensure that the technological growth is compatible with the current recognition. This paper reviews on disability treatment using assistive technology and proposes an extension for the existing cultural model for assistive technology design. © 2014 IEEE. |
2014 |
Bhat, S; Acharya, U R; Adeli, H; Bairy, G M; Adeli, A Autism: Cause factors, early diagnosis and therapies Journal Article Reviews in the Neurosciences, 25 (6), pp. 841-850, 2014, ISSN: 03341763, (cited By 52). Abstract | Links | BibTeX | Tags: 4 Aminobutyric Acid, Adolescent, Agenesis of Corpus Callosum, Animal Assisted Therapy, Anticonvulsive Agent, Article, Assistive Technology, Attention, Autism, Autism Spectrum Disorders, Behaviour Therapy, Biological Marker, Brain, Child Development Disorders, Children, Cognition, Cystine, Developmental Disorders, Diseases, Dolphin, Dolphin Assisted Therapy, DSM-5, Early Diagnosis, Emotion, Facial Expression, Functional Magnetic Resonance Imaging, Functional Neuroimaging, Gaze, Glutathione, Glutathione Disulfide, Human, Infant, Interpersonal Communication, Methionine, Nervous System Inflammation, Neurobiology, Neurofeedback, Oxidative Stress, Pervasive, Physiology, Preschool Child, Priority Journal, Psychoeducation, School Child, Social Interactions, Speech Therapy, Virtual Reality, Zonisamide @article{Bhat2014841, title = {Autism: Cause factors, early diagnosis and therapies}, author = {S Bhat and U R Acharya and H Adeli and G M Bairy and A Adeli}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925284617&doi=10.1515%2frevneuro-2014-0056&partnerID=40&md5=caaa32e66af70e70ec325241d01564c9}, doi = {10.1515/revneuro-2014-0056}, issn = {03341763}, year = {2014}, date = {2014-01-01}, journal = {Reviews in the Neurosciences}, volume = {25}, number = {6}, pages = {841-850}, publisher = {Walter de Gruyter GmbH}, abstract = {Autism spectrum disorder (ASD) is a complex neurobiological disorder characterized by neuropsychological and behavioral deficits. Cognitive impairment, lack of social skills, and stereotyped behavior are the major autistic symptoms, visible after a certain age. It is one of the fastest growing disabilities. Its current prevalence rate in the U.S. estimated by the Centers for Disease Control and Prevention is 1 in 68 births. The genetic and physiological structure of the brain is studied to determine the pathology of autism, but diagnosis of autism at an early age is challenging due to the existing phenotypic and etiological heterogeneity among ASD individuals. Volumetric and neuroimaging techniques are explored to elucidate the neuroanatomy of the ASD brain. Nuroanatomical, neurochemical, and neuroimaging biomarkers can help in the early diagnosis and treatment of ASD. This paper presents a review of the types of autism, etiologies, early detection, and treatment of ASD. © 2014 Walter de Gruyter GmbH.}, note = {cited By 52}, keywords = {4 Aminobutyric Acid, Adolescent, Agenesis of Corpus Callosum, Animal Assisted Therapy, Anticonvulsive Agent, Article, Assistive Technology, Attention, Autism, Autism Spectrum Disorders, Behaviour Therapy, Biological Marker, Brain, Child Development Disorders, Children, Cognition, Cystine, Developmental Disorders, Diseases, Dolphin, Dolphin Assisted Therapy, DSM-5, Early Diagnosis, Emotion, Facial Expression, Functional Magnetic Resonance Imaging, Functional Neuroimaging, Gaze, Glutathione, Glutathione Disulfide, Human, Infant, Interpersonal Communication, Methionine, Nervous System Inflammation, Neurobiology, Neurofeedback, Oxidative Stress, Pervasive, Physiology, Preschool Child, Priority Journal, Psychoeducation, School Child, Social Interactions, Speech Therapy, Virtual Reality, Zonisamide}, pubstate = {published}, tppubtype = {article} } Autism spectrum disorder (ASD) is a complex neurobiological disorder characterized by neuropsychological and behavioral deficits. Cognitive impairment, lack of social skills, and stereotyped behavior are the major autistic symptoms, visible after a certain age. It is one of the fastest growing disabilities. Its current prevalence rate in the U.S. estimated by the Centers for Disease Control and Prevention is 1 in 68 births. The genetic and physiological structure of the brain is studied to determine the pathology of autism, but diagnosis of autism at an early age is challenging due to the existing phenotypic and etiological heterogeneity among ASD individuals. Volumetric and neuroimaging techniques are explored to elucidate the neuroanatomy of the ASD brain. Nuroanatomical, neurochemical, and neuroimaging biomarkers can help in the early diagnosis and treatment of ASD. This paper presents a review of the types of autism, etiologies, early detection, and treatment of ASD. © 2014 Walter de Gruyter GmbH. |
Samat, M R A; Shamsuddin, S; Miskam, M A; Yussof, H Institute of Electrical and Electronics Engineers Inc., 2014, ISBN: 9781479966790, (cited By 1). Abstract | Links | BibTeX | Tags: Algorithms, Autistic Children, Children with Autism, Developmental Disorders, Diseases, Essential Elements, Face Recognition, Face Recognition Algorithms, Robotics, Social Communications, Training Modules @conference{Samat2014, title = {Development of face recognition algorithm for enhancement of social communication of robotic assistive autism therapy}, author = {M R A Samat and S Shamsuddin and M A Miskam and H Yussof}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84922181743&doi=10.1109%2fMHS.2014.7006062&partnerID=40&md5=a995285772a99b9a81c11f49e0a94341}, doi = {10.1109/MHS.2014.7006062}, isbn = {9781479966790}, year = {2014}, date = {2014-01-01}, journal = {2014 International Symposium on Micro-NanoMechatronics and Human Science, MHS 2014}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {In this paper, we propose a face recognition method for tracking, detecting and recognizing the faces of children with Autism Spectrum Disorder (ASD) for robotic assistive therapy application. ASD is a brain developmental disorder that manifests itself through a person's behavior and social-communication skill [1]. Face recognition stage is an essential element in robotic assistive therapy since it is the first interaction step that occurs between autistic children and robot. The algorithm aims to encourage autistic children to interact and to capture their attention using a robot that recognizes their faces. This is to establish a beneficial training environment for autistic children before engaging further in the training module. © 2014 IEEE.}, note = {cited By 1}, keywords = {Algorithms, Autistic Children, Children with Autism, Developmental Disorders, Diseases, Essential Elements, Face Recognition, Face Recognition Algorithms, Robotics, Social Communications, Training Modules}, pubstate = {published}, tppubtype = {conference} } In this paper, we propose a face recognition method for tracking, detecting and recognizing the faces of children with Autism Spectrum Disorder (ASD) for robotic assistive therapy application. ASD is a brain developmental disorder that manifests itself through a person's behavior and social-communication skill [1]. Face recognition stage is an essential element in robotic assistive therapy since it is the first interaction step that occurs between autistic children and robot. The algorithm aims to encourage autistic children to interact and to capture their attention using a robot that recognizes their faces. This is to establish a beneficial training environment for autistic children before engaging further in the training module. © 2014 IEEE. |
2013 |
Shamsuddin, S; Yussof, H; Hanapiah, F A; Mohamed, S A Qualitative method to analyze response in robotic intervention for children with autism Conference 2013, ISBN: 9781479905072, (cited By 2). Abstract | Links | BibTeX | Tags: Autism Intervention, Autistic Children, Behavioral Assessment, Children with Autism, Communication, Diseases, Qualitative Analysis, Qualitative Method, Qualitative Observations, Robotics, Robots, Screening Instruments @conference{Shamsuddin2013324, title = {A Qualitative method to analyze response in robotic intervention for children with autism}, author = {S Shamsuddin and H Yussof and F A Hanapiah and S Mohamed}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84889566919&doi=10.1109%2fROMAN.2013.6628477&partnerID=40&md5=81cd5bf09c75f3d9e6ed4a23ce2362e5}, doi = {10.1109/ROMAN.2013.6628477}, isbn = {9781479905072}, year = {2013}, date = {2013-01-01}, journal = {Proceedings - IEEE International Workshop on Robot and Human Interactive Communication}, pages = {324-325}, abstract = {This paper presents a method to carry out qualitative analysis when evaluating the interaction between child and robot in autism intervention. The technique consists of 24-items of behavioral assessment which was referenced to the Gilliam Autism Rating Scale-Second Edition (GARS-2). GARS-2 is a screening instrument used to identify and diagnose autism. Preliminary results from a pilot study show that this method had allowed qualitative observation to be carried out to compare the behavior of autistic children with and without the presence of a robot. The feasibility of this technique will be further justified through future wide-spread studies involving a larger number of children spanning across the whole spectrum of autism. © 2013 IEEE.}, note = {cited By 2}, keywords = {Autism Intervention, Autistic Children, Behavioral Assessment, Children with Autism, Communication, Diseases, Qualitative Analysis, Qualitative Method, Qualitative Observations, Robotics, Robots, Screening Instruments}, pubstate = {published}, tppubtype = {conference} } This paper presents a method to carry out qualitative analysis when evaluating the interaction between child and robot in autism intervention. The technique consists of 24-items of behavioral assessment which was referenced to the Gilliam Autism Rating Scale-Second Edition (GARS-2). GARS-2 is a screening instrument used to identify and diagnose autism. Preliminary results from a pilot study show that this method had allowed qualitative observation to be carried out to compare the behavior of autistic children with and without the presence of a robot. The feasibility of this technique will be further justified through future wide-spread studies involving a larger number of children spanning across the whole spectrum of autism. © 2013 IEEE. |
Manap, A A; Dehkordi, S R; Rias, R M; Sardan, N A Atlantis Press, 2013, ISBN: 9789462520028, (cited By 0). Abstract | Links | BibTeX | Tags: Autism Spectrum Disorders, Brain Development, Children with Autism, Complex Disorder, Computer Games, Computer Graphics, Computer Vision, Diseases, Education, Games, Semi Structured Interviews, Social Communications, Social Skills, Surveys, Teaching @conference{Manap201326, title = {Computer game approach focusing on social communication skills for children with Autism Spectrum Disorder: An initial study}, author = {A A Manap and S R Dehkordi and R M Rias and N A Sardan}, editor = {Soewito Bououdina B M Chen M.-S. Gaol F.L.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84937138693&partnerID=40&md5=0a35258c8d4d2f61296da695c5ef765f}, isbn = {9789462520028}, year = {2013}, date = {2013-01-01}, journal = {2013 International Conference on Computer Graphics, Visualization, Computer Vision, and Game Technology, VisioGame 2013}, pages = {26-31}, publisher = {Atlantis Press}, abstract = {Autism Spectrum Disorders (ASD) and autism are both general terms for a group of complex disorders of brain development. ASD is characterized by difficulties with communication, social deficits, stereotyped or repetitive behaviours and interests. One of the major reasons behind the push to use technology and multimedia to assist interaction with children diagnosed with ASD is that they have shown a preference for, as well as a fascination with, "visual stimuli" such as computer applications, games, and videos. Primordial purpose of this study is to synthesize a survey regarding social problems and situations faced by children with autism. A number of questionnaires for parents and teachers with a semi-structured interview for five doctors and eleven therapists were conducted to identify basic problems of children with Autism and psychological methods for each problem. © 2014. The authors - Published by Atlantis Press.}, note = {cited By 0}, keywords = {Autism Spectrum Disorders, Brain Development, Children with Autism, Complex Disorder, Computer Games, Computer Graphics, Computer Vision, Diseases, Education, Games, Semi Structured Interviews, Social Communications, Social Skills, Surveys, Teaching}, pubstate = {published}, tppubtype = {conference} } Autism Spectrum Disorders (ASD) and autism are both general terms for a group of complex disorders of brain development. ASD is characterized by difficulties with communication, social deficits, stereotyped or repetitive behaviours and interests. One of the major reasons behind the push to use technology and multimedia to assist interaction with children diagnosed with ASD is that they have shown a preference for, as well as a fascination with, "visual stimuli" such as computer applications, games, and videos. Primordial purpose of this study is to synthesize a survey regarding social problems and situations faced by children with autism. A number of questionnaires for parents and teachers with a semi-structured interview for five doctors and eleven therapists were conducted to identify basic problems of children with Autism and psychological methods for each problem. © 2014. The authors - Published by Atlantis Press. |
Kamaruzaman, M F; Rahman, S H A; Abdullah, K Z; Anwar, R 2013, ISBN: 9781467359689, (cited By 7). Abstract | Links | BibTeX | Tags: Academic Careers, Autistic Children, Calculations, Children with Autism, Conceptual Framework, Curricula, Diseases, Hypothesis Testing, Industrial Applications, Integrated Modeling, Motivation, Self Independence, Students, Theoretical Modeling @conference{Kamaruzaman2013174, title = {Conceptual framework study of basic counting skills based dynamic visual architecture towards autistic children's development}, author = {M F Kamaruzaman and S H A Rahman and K Z Abdullah and R Anwar}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84883104147&doi=10.1109%2fBEIAC.2013.6560108&partnerID=40&md5=4ca69047980f1916b4fea0044cc637f0}, doi = {10.1109/BEIAC.2013.6560108}, isbn = {9781467359689}, year = {2013}, date = {2013-01-01}, journal = {BEIAC 2013 - 2013 IEEE Business Engineering and Industrial Applications Colloquium}, pages = {174-176}, abstract = {For individual with autism, the opportunity to achieve self-determination may be critical to enhance their quality of life. To achieve self-determination and independence, autism patience need to comprehend the learning basic skill system. Since calculation is used in everyday living, understanding the basic calculation skills is one way individual with autism can help achieve independence. The important of calculation especially mathematics in everyday living should not be overlooked for children's with autism. The opportunities to be paid and purchase goods are ways individuals with disabilities can achieve autonomy and independence. For students with autism, learning basic counting skills are important not only for their academic careers but also for their future independence. Our study plans to investigate the counting basic skills based dynamic visual for students with autism that will potentially assist educators, facilitators and curriculum developers to create appropriate instrument and instructional programs to meet students' academic needs. A theoretical model for basic counting skills for autism children's development is to be proposed from the outcome of this study. The next step will be to validate the integrated model proposed which will be conducted through a series of hypothesis testing which includes improved enthusiasm, augmented sense of worth and enhanced analytical. Perhaps more importantly, this research may help students acquire the essential skills they will need for future independence. © 2013 IEEE.}, note = {cited By 7}, keywords = {Academic Careers, Autistic Children, Calculations, Children with Autism, Conceptual Framework, Curricula, Diseases, Hypothesis Testing, Industrial Applications, Integrated Modeling, Motivation, Self Independence, Students, Theoretical Modeling}, pubstate = {published}, tppubtype = {conference} } For individual with autism, the opportunity to achieve self-determination may be critical to enhance their quality of life. To achieve self-determination and independence, autism patience need to comprehend the learning basic skill system. Since calculation is used in everyday living, understanding the basic calculation skills is one way individual with autism can help achieve independence. The important of calculation especially mathematics in everyday living should not be overlooked for children's with autism. The opportunities to be paid and purchase goods are ways individuals with disabilities can achieve autonomy and independence. For students with autism, learning basic counting skills are important not only for their academic careers but also for their future independence. Our study plans to investigate the counting basic skills based dynamic visual for students with autism that will potentially assist educators, facilitators and curriculum developers to create appropriate instrument and instructional programs to meet students' academic needs. A theoretical model for basic counting skills for autism children's development is to be proposed from the outcome of this study. The next step will be to validate the integrated model proposed which will be conducted through a series of hypothesis testing which includes improved enthusiasm, augmented sense of worth and enhanced analytical. Perhaps more importantly, this research may help students acquire the essential skills they will need for future independence. © 2013 IEEE. |
Malik, N A; Shamsuddin, S; Yussof, H; Miskam, M A; Hamid, A C 53 (1), 2013, ISSN: 17578981, (cited By 5). Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, Children with Autism, Diseases, Education, Experiments, Humanoid Robot, Humanoid Robot NAO, Patient Rehabilitation, Pilot Studies, Real Time, Two-Way Communications @conference{Malik2013, title = {Feasibility of using a humanoid robot to elicit communicational response in children with mild autism}, author = {N A Malik and S Shamsuddin and H Yussof and M A Miskam and A C Hamid}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84893647308&doi=10.1088%2f1757-899X%2f53%2f1%2f012077&partnerID=40&md5=c051904f309ab9556d90458decb88f21}, doi = {10.1088/1757-899X/53/1/012077}, issn = {17578981}, year = {2013}, date = {2013-01-01}, journal = {IOP Conference Series: Materials Science and Engineering}, volume = {53}, number = {1}, abstract = {Research evidences are accumulating with regards to the potential use of robots for the rehabilitation of children with autism. The purpose of this paper is to elaborate on the results of communicational response in two children with autism during interaction with the humanoid robot NAO. Both autistic subjects in this study have been diagnosed with mild autism. Following the outcome from our first pilot study; the aim of this current experiment is to explore the application of NAO robot to engage with a child and further teach about emotions through a game-centered and song-based approach. The experiment procedure involved interaction between humanoid robot NAO with each child through a series of four different modules. The observation items are based on ten items selected and referenced to GARS-2 (Gilliam Autism Rating Scale-second edition) and also input from clinicians and therapists. The results clearly indicated that both of the children showed optimistic response through the interaction. Negative responses such as feeling scared or shying away from the robot were not detected. Two-way communication between the child and robot in real time significantly gives positive impact in the responses towards the robot. To conclude, it is feasible to include robot-based interaction specifically to elicit communicational response as a part of the rehabilitation intervention of children with autism. © Published under licence by IOP Publishing Ltd.}, note = {cited By 5}, keywords = {Anthropomorphic Robots, Children with Autism, Diseases, Education, Experiments, Humanoid Robot, Humanoid Robot NAO, Patient Rehabilitation, Pilot Studies, Real Time, Two-Way Communications}, pubstate = {published}, tppubtype = {conference} } Research evidences are accumulating with regards to the potential use of robots for the rehabilitation of children with autism. The purpose of this paper is to elaborate on the results of communicational response in two children with autism during interaction with the humanoid robot NAO. Both autistic subjects in this study have been diagnosed with mild autism. Following the outcome from our first pilot study; the aim of this current experiment is to explore the application of NAO robot to engage with a child and further teach about emotions through a game-centered and song-based approach. The experiment procedure involved interaction between humanoid robot NAO with each child through a series of four different modules. The observation items are based on ten items selected and referenced to GARS-2 (Gilliam Autism Rating Scale-second edition) and also input from clinicians and therapists. The results clearly indicated that both of the children showed optimistic response through the interaction. Negative responses such as feeling scared or shying away from the robot were not detected. Two-way communication between the child and robot in real time significantly gives positive impact in the responses towards the robot. To conclude, it is feasible to include robot-based interaction specifically to elicit communicational response as a part of the rehabilitation intervention of children with autism. © Published under licence by IOP Publishing Ltd. |
2012 |
Hoole, P R P; Pirapaharan, K; Basar, S A; Ismail, R; Liyanage, D L D A; Senanayake, S S H M U L; Hoole, S R H Autism, EEG and brain electromagnetics research Conference 2012, ISBN: 9781467316668, (cited By 11). Abstract | Links | BibTeX | Tags: Biomedical Engineering, Brain, Brain Regions, Classification Accuracy, Diseases, EEG Signals, Electromagnetic Signals, Electromagnetics, Electromagnetism, Frequency Domains, International Group, Multilayer Perception Neural Networks, Neuroimaging, Principal Component Analysis @conference{Hoole2012541, title = {Autism, EEG and brain electromagnetics research}, author = {P R P Hoole and K Pirapaharan and S A Basar and R Ismail and D L D A Liyanage and S S H M U L Senanayake and S R H Hoole}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84876771339&doi=10.1109%2fIECBES.2012.6498036&partnerID=40&md5=9f9390b30b859a90936c66699c1a5115}, doi = {10.1109/IECBES.2012.6498036}, isbn = {9781467316668}, year = {2012}, date = {2012-01-01}, journal = {2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2012}, pages = {541-543}, abstract = {There has been a significant increase in the incidence of autism. We report the work on autism by our international group, on the growing attention paid to EEG based diagnosis and the interest in tracing EEG changes to brain electromagnetic signals (BEMS), seeking the cause of autism and the brain regions of its origin. The time- and frequency domain and principal component analysis (PCA) of these EEG signals with a Multilayer Perception Neural Network (MLP) identifies an autistic subject and helps improve classification accuracy. We show differences between a working brain and a relaxed brain, especially in the Alpha waves used for diagnosis. © 2012 IEEE.}, note = {cited By 11}, keywords = {Biomedical Engineering, Brain, Brain Regions, Classification Accuracy, Diseases, EEG Signals, Electromagnetic Signals, Electromagnetics, Electromagnetism, Frequency Domains, International Group, Multilayer Perception Neural Networks, Neuroimaging, Principal Component Analysis}, pubstate = {published}, tppubtype = {conference} } There has been a significant increase in the incidence of autism. We report the work on autism by our international group, on the growing attention paid to EEG based diagnosis and the interest in tracing EEG changes to brain electromagnetic signals (BEMS), seeking the cause of autism and the brain regions of its origin. The time- and frequency domain and principal component analysis (PCA) of these EEG signals with a Multilayer Perception Neural Network (MLP) identifies an autistic subject and helps improve classification accuracy. We show differences between a working brain and a relaxed brain, especially in the Alpha waves used for diagnosis. © 2012 IEEE. |
2011 |
Razali, N; Wahab, A 2D Affective Space Model (ASM) for detecting autistic children Conference 2011, ISBN: 9781612848433, (cited By 8). Abstract | Links | BibTeX | Tags: Autistic Children, Brain Disorders, Brain Imaging, Brain Imaging Techniques, Brain Signals, Children with Autism, Consumer Electronics, Data Collection, Diseases, Electroencephalogram, Electroencephalography, Feature Extraction, Frequency Domains, Functional Magnetic Resonance Imaging, Gaussian Mixture Model, Magnetic Resonance Imaging, Multi Layer Perceptron, Multilayer Perceptron, Multilayers, Positron Emission Tomography, Resonance, Space Models, Verification Results @conference{Razali2011536, title = {2D Affective Space Model (ASM) for detecting autistic children}, author = {N Razali and A Wahab}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052392399&doi=10.1109%2fISCE.2011.5973888&partnerID=40&md5=f6ea401148e6558b861e4df6407e527e}, doi = {10.1109/ISCE.2011.5973888}, isbn = {9781612848433}, year = {2011}, date = {2011-01-01}, journal = {Proceedings of the International Symposium on Consumer Electronics, ISCE}, pages = {536-541}, abstract = {There are many research works have been done on autism cases using brain imaging techniques. In this paper, the Electroencephalogram (EEG) was used to understand and analyze the functionality of the brain to identify or detect brain disorder for autism in term of motor imitation. Thus, the portability and affordability of the EEG equipment makes it a better choice in comparison with other brain imaging device such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET) and megnetoencephalography (MEG). Data collection consists of both autistic and normal children with the total of 6 children for each group. All subjects were asked to clinch their hand by following video stimuli which presented in 1 minute time. Gaussian mixture model was used as a method of feature extraction for analyzing the brain signals in frequency domain. Then, the extraction data were classified using multilayer perceptron (MLP). According to the verification result, the percentage of discriminating between both groups is up to 85% in average by using k-fold validation. © 2011 IEEE.}, note = {cited By 8}, keywords = {Autistic Children, Brain Disorders, Brain Imaging, Brain Imaging Techniques, Brain Signals, Children with Autism, Consumer Electronics, Data Collection, Diseases, Electroencephalogram, Electroencephalography, Feature Extraction, Frequency Domains, Functional Magnetic Resonance Imaging, Gaussian Mixture Model, Magnetic Resonance Imaging, Multi Layer Perceptron, Multilayer Perceptron, Multilayers, Positron Emission Tomography, Resonance, Space Models, Verification Results}, pubstate = {published}, tppubtype = {conference} } There are many research works have been done on autism cases using brain imaging techniques. In this paper, the Electroencephalogram (EEG) was used to understand and analyze the functionality of the brain to identify or detect brain disorder for autism in term of motor imitation. Thus, the portability and affordability of the EEG equipment makes it a better choice in comparison with other brain imaging device such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET) and megnetoencephalography (MEG). Data collection consists of both autistic and normal children with the total of 6 children for each group. All subjects were asked to clinch their hand by following video stimuli which presented in 1 minute time. Gaussian mixture model was used as a method of feature extraction for analyzing the brain signals in frequency domain. Then, the extraction data were classified using multilayer perceptron (MLP). According to the verification result, the percentage of discriminating between both groups is up to 85% in average by using k-fold validation. © 2011 IEEE. |
Shams, Khazaal W; Rahman, Abdul A W Characterizing autistic disorder based on principle component analysis Conference 2011, ISBN: 9781457714184, (cited By 6). Abstract | Links | BibTeX | Tags: Autism, Brain Function, Brain Signals, Classification Process, Data Dimensions, Diseases, Electroencephalogram Signals, Electroencephalography, Frequency Domain Analysis, Industrial Electronics, Motor Movements, Motor Tasks, PCA, Principal Component Analysis, Signal Detection, Time Frequency Domain @conference{KhazaalShams2011653, title = {Characterizing autistic disorder based on principle component analysis}, author = {W Khazaal Shams and A W Abdul Rahman}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84855644760&doi=10.1109%2fISIEA.2011.6108797&partnerID=40&md5=c486566e2d7ff404d830704c0b404067}, doi = {10.1109/ISIEA.2011.6108797}, isbn = {9781457714184}, year = {2011}, date = {2011-01-01}, journal = {2011 IEEE Symposium on Industrial Electronics and Applications, ISIEA 2011}, pages = {653-657}, abstract = {Autism is often diagnosed during preschool or toddled age. This diagnosis often depends on behavioral test. It is known that individuals with autism have abnormal brain signals different from typical persons yet this difference in signals is slight that it is often difficult to distinguish from the normal. However, Electroencephalogram (EEG) signals have a lot of information which reflect the behavior of brain functions which therefore captures the marker for autism, help to early diagnose and speed the treatment. This work investigates and compares classification process for autism in open-eyed tasks and motor movement by using Principle Component Analysis (PCA) for feature extracted in Time-frequency domain to reduce data dimension. The results show that the proposed method gives accuracy in the range 90-100% for autism and normal children in motor task and around 90% to detect normal in open-eyed tasks though difficult to detect autism in this task. © 2011 IEEE.}, note = {cited By 6}, keywords = {Autism, Brain Function, Brain Signals, Classification Process, Data Dimensions, Diseases, Electroencephalogram Signals, Electroencephalography, Frequency Domain Analysis, Industrial Electronics, Motor Movements, Motor Tasks, PCA, Principal Component Analysis, Signal Detection, Time Frequency Domain}, pubstate = {published}, tppubtype = {conference} } Autism is often diagnosed during preschool or toddled age. This diagnosis often depends on behavioral test. It is known that individuals with autism have abnormal brain signals different from typical persons yet this difference in signals is slight that it is often difficult to distinguish from the normal. However, Electroencephalogram (EEG) signals have a lot of information which reflect the behavior of brain functions which therefore captures the marker for autism, help to early diagnose and speed the treatment. This work investigates and compares classification process for autism in open-eyed tasks and motor movement by using Principle Component Analysis (PCA) for feature extracted in Time-frequency domain to reduce data dimension. The results show that the proposed method gives accuracy in the range 90-100% for autism and normal children in motor task and around 90% to detect normal in open-eyed tasks though difficult to detect autism in this task. © 2011 IEEE. |
Iradah, Siti I; Rabiah, A K EduTism: An assistive educational system for the treatment of autism children with intelligent approach Journal Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7067 LNCS (PART 2), pp. 193-204, 2011, ISSN: 03029743, (cited By 3). Abstract | Links | BibTeX | Tags: Algorithms, Assistive, Autism Intervention, Data Collection, Diseases, E-learning, Education, Educational Software, Educational Systems, High-Functioning Autism, Information Science, Intelligent Approach, Malaysia, Multimedia Systems, Rule Based, Software Testing, Student Performance, Students @article{SitiIradah2011193, title = {EduTism: An assistive educational system for the treatment of autism children with intelligent approach}, author = {I Siti Iradah and A K Rabiah}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-81255214646&doi=10.1007%2f978-3-642-25200-6_19&partnerID=40&md5=85447136ace048f4543c86a103c8a786}, doi = {10.1007/978-3-642-25200-6_19}, issn = {03029743}, year = {2011}, date = {2011-01-01}, journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {7067 LNCS}, number = {PART 2}, pages = {193-204}, abstract = {This paper presents the development of an assistive educational system with intelligent approach which can be a basic electronic training and treatment tool to assist children with high-functioning autism. The plan is to bring these changes through the use of rules based algorithm as an approach to decide which level difficulty of the system should go according to the autism student performance based on the percentage of score. By applying this approach, the system will be able to monitor and analyze the performance of intelligent of autism student's capabilities. The system is capable to control the particular level of the autism students should play. It is capable to replace the teacher's responsibilities in terms of monitoring the student's progress and performance. Testing was conducted in Autism Intervention Programme of The National Autism Society of Malaysia (NASOM) at Malacca branch. Results and findings from this testing support the idea that educational software may be one of an effective and practical tool for teaching academic skills to autism children. Having programssuch asEduTism can improve effectiveness and efficiency of data collection tracking and reporting for the teachers and parents. © 2011 Springer-Verlag.}, note = {cited By 3}, keywords = {Algorithms, Assistive, Autism Intervention, Data Collection, Diseases, E-learning, Education, Educational Software, Educational Systems, High-Functioning Autism, Information Science, Intelligent Approach, Malaysia, Multimedia Systems, Rule Based, Software Testing, Student Performance, Students}, pubstate = {published}, tppubtype = {article} } This paper presents the development of an assistive educational system with intelligent approach which can be a basic electronic training and treatment tool to assist children with high-functioning autism. The plan is to bring these changes through the use of rules based algorithm as an approach to decide which level difficulty of the system should go according to the autism student performance based on the percentage of score. By applying this approach, the system will be able to monitor and analyze the performance of intelligent of autism student's capabilities. The system is capable to control the particular level of the autism students should play. It is capable to replace the teacher's responsibilities in terms of monitoring the student's progress and performance. Testing was conducted in Autism Intervention Programme of The National Autism Society of Malaysia (NASOM) at Malacca branch. Results and findings from this testing support the idea that educational software may be one of an effective and practical tool for teaching academic skills to autism children. Having programssuch asEduTism can improve effectiveness and efficiency of data collection tracking and reporting for the teachers and parents. © 2011 Springer-Verlag. |
Ismail, L; Shamsuddin, S; Yussof, H; Hashim, H; Bahari, S; Jaafar, A; Zahari, I Face detection technique of Humanoid Robot NAO for application in robotic assistive therapy Conference 2011, ISBN: 9781457716423, (cited By 14). Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, Assistive, Autism Spectrum Disorders, Autistic Children, Cameras, Children with Autism, Communication, Concentration Levels, Control Systems, Cutting Edges, Detection Tools, Developmental Disorders, Diseases, Face Detection, Face Recognition, Graphical User Interfaces, Humanoid Robot, Robotics, Social Interactions @conference{Ismail2011517, title = {Face detection technique of Humanoid Robot NAO for application in robotic assistive therapy}, author = {L Ismail and S Shamsuddin and H Yussof and H Hashim and S Bahari and A Jaafar and I Zahari}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84862067305&doi=10.1109%2fICCSCE.2011.6190580&partnerID=40&md5=954caf63c5c5f7f05062436598a32a91}, doi = {10.1109/ICCSCE.2011.6190580}, isbn = {9781457716423}, year = {2011}, date = {2011-01-01}, journal = {Proceedings - 2011 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2011}, pages = {517-521}, abstract = {This paper proposed a face detection method for tracking the faces of children with Autism Spectrum Disorder in a robotic assistive therapy. The face detection is a novel approach in robotic assistive therapy involving autistic children since it is believe that those children will positively react with high-end devices, gadget and cutting edge devices. The intention of tracking the autistic children's faces is to measure the concentration level of the children in social interaction and communication since everyone knows that those children are suffering from communication disabilities and deficits due to brain developmental disorder. Humanoid Robot Nao with 573.2mm height equipped with 2 internal cameras is utilized for this research. The face detection tools in choregraphe and telepathe based on Graphical User Interface (GUI) module is used in this study. The non-verbal interaction between humanoid robot and autistic children is recorded by using 2 internal cameras from the robot's head. The interaction is going to take about 30 minutes and supervised by occupational therapist and certified psychologist. The autistic children will be introduced to the Humanoid Robot Nao and their reaction will be recorded simultaneously while the robot is trying to track their faces. © 2011 IEEE.}, note = {cited By 14}, keywords = {Anthropomorphic Robots, Assistive, Autism Spectrum Disorders, Autistic Children, Cameras, Children with Autism, Communication, Concentration Levels, Control Systems, Cutting Edges, Detection Tools, Developmental Disorders, Diseases, Face Detection, Face Recognition, Graphical User Interfaces, Humanoid Robot, Robotics, Social Interactions}, pubstate = {published}, tppubtype = {conference} } This paper proposed a face detection method for tracking the faces of children with Autism Spectrum Disorder in a robotic assistive therapy. The face detection is a novel approach in robotic assistive therapy involving autistic children since it is believe that those children will positively react with high-end devices, gadget and cutting edge devices. The intention of tracking the autistic children's faces is to measure the concentration level of the children in social interaction and communication since everyone knows that those children are suffering from communication disabilities and deficits due to brain developmental disorder. Humanoid Robot Nao with 573.2mm height equipped with 2 internal cameras is utilized for this research. The face detection tools in choregraphe and telepathe based on Graphical User Interface (GUI) module is used in this study. The non-verbal interaction between humanoid robot and autistic children is recorded by using 2 internal cameras from the robot's head. The interaction is going to take about 30 minutes and supervised by occupational therapist and certified psychologist. The autistic children will be introduced to the Humanoid Robot Nao and their reaction will be recorded simultaneously while the robot is trying to track their faces. © 2011 IEEE. |
2010 |
Othman, M; Wahab, A Affective face processing analysis in autism using electroencephalogram Conference 2010, ISBN: 9789791948913, (cited By 7). Abstract | Links | BibTeX | Tags: Affective Face Processing, Analysis Results, Autism Spectrum Disorders, Brain Wave, Diseases, Electroencephalogram, Electroencephalography, Emotion, Emotion Models, Eye Contact, Facial Expression, Human Emotion, Information Technology @conference{Othman2010, title = {Affective face processing analysis in autism using electroencephalogram}, author = {M Othman and A Wahab}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052372671&doi=10.1109%2fICT4M.2010.5971907&partnerID=40&md5=4d5f8a317d6a9c93e1ab7186a9b99b52}, doi = {10.1109/ICT4M.2010.5971907}, isbn = {9789791948913}, year = {2010}, date = {2010-01-01}, journal = {Proceeding of the 3rd International Conference on Information and Communication Technology for the Moslem World: ICT Connecting Cultures, ICT4M 2010}, pages = {E23-E27}, abstract = {Past research in the area of psychology has indicated the inability of Autism Spectrum Disorder (ASD) patients for interpreting other people's emotion. This impairment is due to their lack of social motivation and eye contact during communication, causing insufficient information to the brain for interpreting emotional faces. This paper investigates human brainwaves for understanding affective face processing of ASD children. Pattern classification results are explained based on the 2-dimensional emotion model. The 2-dimensional model explains human emotion in terms of the pleasant/ unpleasantness (or valence) and intensity (or arousal). Analysis results revealed that emotion of the non-autistic group is altered towards matching the affective faces currently displayed on the computer monitor. Emotion dynamics of ASD children, however, indicated the trend for reversed valence while watching emotionally related facial expressions. © 2010 IEEE.}, note = {cited By 7}, keywords = {Affective Face Processing, Analysis Results, Autism Spectrum Disorders, Brain Wave, Diseases, Electroencephalogram, Electroencephalography, Emotion, Emotion Models, Eye Contact, Facial Expression, Human Emotion, Information Technology}, pubstate = {published}, tppubtype = {conference} } Past research in the area of psychology has indicated the inability of Autism Spectrum Disorder (ASD) patients for interpreting other people's emotion. This impairment is due to their lack of social motivation and eye contact during communication, causing insufficient information to the brain for interpreting emotional faces. This paper investigates human brainwaves for understanding affective face processing of ASD children. Pattern classification results are explained based on the 2-dimensional emotion model. The 2-dimensional model explains human emotion in terms of the pleasant/ unpleasantness (or valence) and intensity (or arousal). Analysis results revealed that emotion of the non-autistic group is altered towards matching the affective faces currently displayed on the computer monitor. Emotion dynamics of ASD children, however, indicated the trend for reversed valence while watching emotionally related facial expressions. © 2010 IEEE. |
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2020 |
Augmented reality for learning of children and adolescents with autism spectrum disorder (ASD): A systematic review Journal Article IEEE Access, 8 , pp. 78779-78807, 2020, ISSN: 21693536, (cited By 0). |
Autism Spectrum Disorder Classification in Videos: A Hybrid of Temporal Coherency Deep Networks and Self-organizing Dual Memory Approach Journal Article Lecture Notes in Electrical Engineering, 621 , pp. 421-430, 2020, ISSN: 18761100, (cited By 0). |
2019 |
Institute of Electrical and Electronics Engineers Inc., 2019, ISBN: 9781728108513, (cited By 0). |
A Review on Gamification Design Framework: How They Incorporated for Autism Children Conference Institute of Electrical and Electronics Engineers Inc., 2019, ISBN: 9781728126104, (cited By 0). |
A study on mobile applications developed for children with autism Journal Article Advances in Intelligent Systems and Computing, 843 , pp. 772-780, 2019, ISSN: 21945357, (cited By 0). |
Universal Access in the Information Society, 2019, ISSN: 16155289, (cited By 2). |
2018-October , Institute of Electrical and Electronics Engineers Inc., 2019, ISSN: 21593442, (cited By 0). |
App4Autism: An integrated assistive technology with heart rate monitoring for children with autism Journal Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11870 LNCS , pp. 498-512, 2019, ISSN: 03029743, (cited By 0). |
Classification of adults with autism spectrum disorder using deep neural network Conference Institute of Electrical and Electronics Engineers Inc., 2019, ISBN: 9781728130415, (cited By 0). |
Institute of Electrical and Electronics Engineers Inc., 2019, ISBN: 9781538679661, (cited By 2). |
Evaluation on Machine Learning Algorithms for Classification of Autism Spectrum Disorder (ASD) Conference 1372 (1), Institute of Physics Publishing, 2019, ISSN: 17426588, (cited By 0). |
2018 |
150 , EDP Sciences, 2018, ISSN: 2261236X, (cited By 0). |
Design and development of therapeutic aid tools using human-machine interaction approach for children with autism spectrum disorder Journal Article Advances in Intelligent Systems and Computing, 739 , pp. 530-537, 2018, ISSN: 21945357, (cited By 0). |
Evaluation of video modeling application to teach social interaction skills to autistic children Journal Article Communications in Computer and Information Science, 886 , pp. 125-135, 2018, ISSN: 18650929, (cited By 0). |
2017 |
Institute of Electrical and Electronics Engineers Inc., 2017, ISBN: 9781509045211, (cited By 3). |
A Review of the Ambit of Politics in Social Robotics Conference 105 , Elsevier B.V., 2017, ISSN: 18770509, (cited By 3). |
2018-January , Institute of Electrical and Electronics Engineers Inc., 2017, ISBN: 9781538607657, (cited By 1). |
Development of three dimensional gait pattern in autism children - a review Conference Institute of Electrical and Electronics Engineers Inc., 2017, ISBN: 9781509011780, (cited By 0). |
Efficacy of DTT by using touchscreen learning numeracy App for children with autism Conference Institute of Electrical and Electronics Engineers Inc., 2017, ISBN: 9781509015955, (cited By 1). |
135 , EDP Sciences, 2017, ISSN: 2261236X, (cited By 1). |
Institute of Electrical and Electronics Engineers Inc., 2017, ISBN: 9781509009251, (cited By 0). |
2016 |
Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781479966783, (cited By 1). |
Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781509015436, (cited By 4). |
Classification of autism children gait patterns using Neural Network and Support Vector Machine Conference Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781509015436, (cited By 5). |
Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781509016365, (cited By 2). |
Development phase of mobile numerical application for children with autism: Math4Autism Conference Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781509051342, (cited By 1). |
2015 |
A content validated tool to observe autism behavior in child-robot interaction Conference 2015-November , Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781467367042, (cited By 1). |
A review on employee benefits for working parents with autistic children Conference Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479957651, (cited By 1). |
ASKNAO apps targeting at social skills development for children with autism Conference 2015-October , IEEE Computer Society, 2015, ISSN: 21618070, (cited By 3). |
Autism children: Cost and benefit analysis of using humanoid in Malaysia Conference Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479957651, (cited By 3). |
Autism severity level detection using fuzzy expert system Conference Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479957651, (cited By 2). |
AUTISTHERAPIBOT: Autonomous robotic autism therapists assistant for autistic children Conference Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479957651, (cited By 1). |
Autistic Children's Kansei Responses Towards Humanoid-Robot as Teaching Mediator Conference 76 , Elsevier B.V., 2015, ISSN: 18770509, (cited By 6). |
Can spatiotemporal gait analysis identify a child with Autistic Spectrum Disorder? Conference Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479957651, (cited By 0). |
Digital Game-Based Learning for Low Functioning Autism Children in Learning Al-Quran Conference Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479928231, (cited By 4). |
Dynamic screening of autistic children in various mental states using pattern of connectivity between brain regions Journal Article Applied Soft Computing Journal, 32 , pp. 335-346, 2015, ISSN: 15684946, (cited By 6). |
Experimental Framework for the Categorization of Special Education Programs of ASKNAO Conference 76 , Elsevier B.V., 2015, ISSN: 18770509, (cited By 4). |
Extending cultural model of assistive technology design for autism treatment Conference Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479957651, (cited By 1). |
2014 |
Autism: Cause factors, early diagnosis and therapies Journal Article Reviews in the Neurosciences, 25 (6), pp. 841-850, 2014, ISSN: 03341763, (cited By 52). |
Institute of Electrical and Electronics Engineers Inc., 2014, ISBN: 9781479966790, (cited By 1). |
2013 |
A Qualitative method to analyze response in robotic intervention for children with autism Conference 2013, ISBN: 9781479905072, (cited By 2). |
Atlantis Press, 2013, ISBN: 9789462520028, (cited By 0). |
2013, ISBN: 9781467359689, (cited By 7). |
53 (1), 2013, ISSN: 17578981, (cited By 5). |
2012 |
Autism, EEG and brain electromagnetics research Conference 2012, ISBN: 9781467316668, (cited By 11). |
2011 |
2D Affective Space Model (ASM) for detecting autistic children Conference 2011, ISBN: 9781612848433, (cited By 8). |
Characterizing autistic disorder based on principle component analysis Conference 2011, ISBN: 9781457714184, (cited By 6). |
EduTism: An assistive educational system for the treatment of autism children with intelligent approach Journal Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7067 LNCS (PART 2), pp. 193-204, 2011, ISSN: 03029743, (cited By 3). |
Face detection technique of Humanoid Robot NAO for application in robotic assistive therapy Conference 2011, ISBN: 9781457716423, (cited By 14). |
2010 |
Affective face processing analysis in autism using electroencephalogram Conference 2010, ISBN: 9789791948913, (cited By 7). |