2020 |
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{Liang2020421, title = {Autism Spectrum Disorder Classification in Videos: A Hybrid of Temporal Coherency Deep Networks and Self-organizing Dual Memory Approach}, author = {S Liang and C K Loo and A Q Md Sabri}, editor = {Kim H -Y Kim K.J.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077496650&doi=10.1007%2f978-981-15-1465-4_42&partnerID=40&md5=8d885d212faf9e5a9d686c58a2e4eecd}, doi = {10.1007/978-981-15-1465-4_42}, issn = {18761100}, year = {2020}, date = {2020-01-01}, journal = {Lecture Notes in Electrical Engineering}, volume = {621}, pages = {421-430}, publisher = {Springer}, abstract = {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.}, note = {cited By 0}, keywords = {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}, pubstate = {published}, tppubtype = {article} } 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 |
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. |
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 |
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. |
Hariharan, M; Sindhu, R; Vijean, V; Yazid, H; Nadarajaw, T; Yaacob, S; Polat, K Improved binary dragonfly optimization algorithm and wavelet packet based non-linear features for infant cry classification Journal Article Computer Methods and Programs in Biomedicine, 155 , pp. 39-51, 2018, ISSN: 01692607, (cited By 21). Abstract | Links | BibTeX | Tags: Accidents, Algorithms, Article, Artificial Neural Network, Asphyxia, Binary Dragonfly Optimization Aalgorithm, Classification (of information), Classification Algorithm, Classifier, Coding, Computer-Assisted, Constants and Coefficients, Crying, Database Systems, Databases, Deafness, Diagnosis, Energy, Entropy, Extraction, Extreme Learning Machine, Factual, Factual Database, Feature Extraction, Feature Selection Methods, Fuzzy System, Hearing Impairment, Human, Hunger, Infant, Infant Cry, Infant Cry Classifications, Jaundice, Kernel Method, Learning, Linear Predictive Coding, Machine Learning, Mathematical Transformations, Mel Frequency Cepstral Coefficient, Mel Frequency Cepstral Coefficients, Multi-Class Classification, Neural Networks, Nonlinear Dynamics, Nonlinear System, Optimization, Pain, Pathophysiology, Prematurity, Reproducibility, Reproducibility of Results, Signal Processing, Speech Recognition, Wavelet Analysis, Wavelet Packet, Wavelet Packet Transforms @article{Hariharan201839, title = {Improved binary dragonfly optimization algorithm and wavelet packet based non-linear features for infant cry classification}, author = {M Hariharan and R Sindhu and V Vijean and H Yazid and T Nadarajaw and S Yaacob and K Polat}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85036611215&doi=10.1016%2fj.cmpb.2017.11.021&partnerID=40&md5=1f3b17817b00f07cadad6eb61c0f4bf9}, doi = {10.1016/j.cmpb.2017.11.021}, issn = {01692607}, year = {2018}, date = {2018-01-01}, journal = {Computer Methods and Programs in Biomedicine}, volume = {155}, pages = {39-51}, publisher = {Elsevier Ireland Ltd}, abstract = {Background and objective Infant cry signal carries several levels of information about the reason for crying (hunger, pain, sleepiness and discomfort) or the pathological status (asphyxia, deaf, jaundice, premature condition and autism, etc.) of an infant and therefore suited for early diagnosis. In this work, combination of wavelet packet based features and Improved Binary Dragonfly Optimization based feature selection method was proposed to classify the different types of infant cry signals. Methods Cry signals from 2 different databases were utilized. First database contains 507 cry samples of normal (N), 340 cry samples of asphyxia (A), 879 cry samples of deaf (D), 350 cry samples of hungry (H) and 192 cry samples of pain (P). Second database contains 513 cry samples of jaundice (J), 531 samples of premature (Prem) and 45 samples of normal (N). Wavelet packet transform based energy and non-linear entropies (496 features), Linear Predictive Coding (LPC) based cepstral features (56 features), Mel-frequency Cepstral Coefficients (MFCCs) were extracted (16 features). The combined feature set consists of 568 features. To overcome the curse of dimensionality issue, improved binary dragonfly optimization algorithm (IBDFO) was proposed to select the most salient attributes or features. Finally, Extreme Learning Machine (ELM) kernel classifier was used to classify the different types of infant cry signals using all the features and highly informative features as well. Results Several experiments of two-class and multi-class classification of cry signals were conducted. In binary or two-class experiments, maximum accuracy of 90.18% for H Vs P, 100% for A Vs N, 100% for D Vs N and 97.61% J Vs Prem was achieved using the features selected (only 204 features out of 568) by IBDFO. For the classification of multiple cry signals (multi-class problem), the selected features could differentiate between three classes (N, A & D) with the accuracy of 100% and seven classes with the accuracy of 97.62%. Conclusion The experimental results indicated that the proposed combination of feature extraction and selection method offers suitable classification accuracy and may be employed to detect the subtle changes in the cry signals. © 2017 Elsevier B.V.}, note = {cited By 21}, keywords = {Accidents, Algorithms, Article, Artificial Neural Network, Asphyxia, Binary Dragonfly Optimization Aalgorithm, Classification (of information), Classification Algorithm, Classifier, Coding, Computer-Assisted, Constants and Coefficients, Crying, Database Systems, Databases, Deafness, Diagnosis, Energy, Entropy, Extraction, Extreme Learning Machine, Factual, Factual Database, Feature Extraction, Feature Selection Methods, Fuzzy System, Hearing Impairment, Human, Hunger, Infant, Infant Cry, Infant Cry Classifications, Jaundice, Kernel Method, Learning, Linear Predictive Coding, Machine Learning, Mathematical Transformations, Mel Frequency Cepstral Coefficient, Mel Frequency Cepstral Coefficients, Multi-Class Classification, Neural Networks, Nonlinear Dynamics, Nonlinear System, Optimization, Pain, Pathophysiology, Prematurity, Reproducibility, Reproducibility of Results, Signal Processing, Speech Recognition, Wavelet Analysis, Wavelet Packet, Wavelet Packet Transforms}, pubstate = {published}, tppubtype = {article} } Background and objective Infant cry signal carries several levels of information about the reason for crying (hunger, pain, sleepiness and discomfort) or the pathological status (asphyxia, deaf, jaundice, premature condition and autism, etc.) of an infant and therefore suited for early diagnosis. In this work, combination of wavelet packet based features and Improved Binary Dragonfly Optimization based feature selection method was proposed to classify the different types of infant cry signals. Methods Cry signals from 2 different databases were utilized. First database contains 507 cry samples of normal (N), 340 cry samples of asphyxia (A), 879 cry samples of deaf (D), 350 cry samples of hungry (H) and 192 cry samples of pain (P). Second database contains 513 cry samples of jaundice (J), 531 samples of premature (Prem) and 45 samples of normal (N). Wavelet packet transform based energy and non-linear entropies (496 features), Linear Predictive Coding (LPC) based cepstral features (56 features), Mel-frequency Cepstral Coefficients (MFCCs) were extracted (16 features). The combined feature set consists of 568 features. To overcome the curse of dimensionality issue, improved binary dragonfly optimization algorithm (IBDFO) was proposed to select the most salient attributes or features. Finally, Extreme Learning Machine (ELM) kernel classifier was used to classify the different types of infant cry signals using all the features and highly informative features as well. Results Several experiments of two-class and multi-class classification of cry signals were conducted. In binary or two-class experiments, maximum accuracy of 90.18% for H Vs P, 100% for A Vs N, 100% for D Vs N and 97.61% J Vs Prem was achieved using the features selected (only 204 features out of 568) by IBDFO. For the classification of multiple cry signals (multi-class problem), the selected features could differentiate between three classes (N, A & D) with the accuracy of 100% and seven classes with the accuracy of 97.62%. Conclusion The experimental results indicated that the proposed combination of feature extraction and selection method offers suitable classification accuracy and may be employed to detect the subtle changes in the cry signals. © 2017 Elsevier B.V. |
2017 |
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. |
Bhagat, V; Haque, M; Simbak, N B; Husain, R Emotional regulation in autism spectrum disorders: A new proposed model for regulating emotions through parent education Journal Article Journal of Global Pharma Technology, 9 (7), pp. 32-43, 2017, ISSN: 09758542, (cited By 0). Abstract | Links | BibTeX | Tags: Adaptive Behavior, Amygdala, Autism, Awareness, Cognition, Comorbidity, Conceptual Framework, Cost Benefit Analysis, Education, Emotion, Emotional Disorder, Emotionality, Health Care, Health Promotion, Human, Impulsiveness, Learning, Motivation, Parent Education, Perception, Practice Guideline, Prefrontal Cortex, Prevalence, Problem Behavior, Psychoeducation, Psychological Well Being, Review, Sex Difference, Social Behaviour, Social Cognition, Social Competence, Social Learning @article{Bhagat201732, title = {Emotional regulation in autism spectrum disorders: A new proposed model for regulating emotions through parent education}, author = {V Bhagat and M Haque and N B Simbak and R Husain}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021786235&partnerID=40&md5=ece2d7c28018f0c4526810e08e314461}, issn = {09758542}, year = {2017}, date = {2017-01-01}, journal = {Journal of Global Pharma Technology}, volume = {9}, number = {7}, pages = {32-43}, publisher = {Journal of Global Pharma Technology}, abstract = {Autism spectrum disorders (ASD) may affect all spheres of a child's life. One of the areas of the behavioral spectrum need to be focused is affected. Thus, the study is enthused in impaired emotional regulation (ER) affecting children with ASD. The significance of ER is related to that promoting adaptive behavior in children; indeed, disturbed ER in ASD children leads to emotional and behavioral problems. Commonly children with ASD lack adaptive ER strategies thus they react impulsively and inadequately to emotional stimuli thus it affects their psychological well-being. Though ER in ASD children is intrinsic the nurturing of these children with an understanding of ER can promote better psychological wellbeing. Thus, study objectives to examine a) the impact of ASD on their ER b) the impact of ER on the psychological wellbeing of children with ASD c) To develop awareness among these parents regarding the impact of ER on the psychological wellbeing of their ASD child. d) To propose a new model of parental education about ER and its significance on psychological wellbeing of ASD children. This study takes a base on the keenly examined past evidence on impaired ER in ASD children and its impact on the psychological wellbeing. Proposal for aiding ER through parental education has introduced. The conclusion drawn in this study is that the intervention can be more promising with educating parents regarding ER, may help their child to gain maximum from therapeutic intervention. The new proposed model of intervention extends the further scope for research in this regard. © 2009-2017, JGPT.}, note = {cited By 0}, keywords = {Adaptive Behavior, Amygdala, Autism, Awareness, Cognition, Comorbidity, Conceptual Framework, Cost Benefit Analysis, Education, Emotion, Emotional Disorder, Emotionality, Health Care, Health Promotion, Human, Impulsiveness, Learning, Motivation, Parent Education, Perception, Practice Guideline, Prefrontal Cortex, Prevalence, Problem Behavior, Psychoeducation, Psychological Well Being, Review, Sex Difference, Social Behaviour, Social Cognition, Social Competence, Social Learning}, pubstate = {published}, tppubtype = {article} } Autism spectrum disorders (ASD) may affect all spheres of a child's life. One of the areas of the behavioral spectrum need to be focused is affected. Thus, the study is enthused in impaired emotional regulation (ER) affecting children with ASD. The significance of ER is related to that promoting adaptive behavior in children; indeed, disturbed ER in ASD children leads to emotional and behavioral problems. Commonly children with ASD lack adaptive ER strategies thus they react impulsively and inadequately to emotional stimuli thus it affects their psychological well-being. Though ER in ASD children is intrinsic the nurturing of these children with an understanding of ER can promote better psychological wellbeing. Thus, study objectives to examine a) the impact of ASD on their ER b) the impact of ER on the psychological wellbeing of children with ASD c) To develop awareness among these parents regarding the impact of ER on the psychological wellbeing of their ASD child. d) To propose a new model of parental education about ER and its significance on psychological wellbeing of ASD children. This study takes a base on the keenly examined past evidence on impaired ER in ASD children and its impact on the psychological wellbeing. Proposal for aiding ER through parental education has introduced. The conclusion drawn in this study is that the intervention can be more promising with educating parents regarding ER, may help their child to gain maximum from therapeutic intervention. The new proposed model of intervention extends the further scope for research in this regard. © 2009-2017, JGPT. |
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. |
Raja, P; Saringat, M Z; Mustapha, A; Zainal, A 226 (1), Institute of Physics Publishing, 2017, ISSN: 17578981, (cited By 0). Abstract | Links | BibTeX | Tags: Agile Development, Autism Spectrum Disorders, Brain, Development Activity, Digital Representations, Diseases, Education, Instant Messaging, Learning, Mobile Applications, Verbal Communication @conference{Raja2017, title = {Prospect: A Picture Exchange Communication System (PECS)-based Instant Messaging Application for Autism Spectrum Condition}, author = {P Raja and M Z Saringat and A Mustapha and A Zainal}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028640453&doi=10.1088%2f1757-899X%2f226%2f1%2f012088&partnerID=40&md5=06b8f5c7d5f5ee64b938b4aea1adfe51}, doi = {10.1088/1757-899X/226/1/012088}, issn = {17578981}, year = {2017}, date = {2017-01-01}, journal = {IOP Conference Series: Materials Science and Engineering}, volume = {226}, number = {1}, publisher = {Institute of Physics Publishing}, abstract = {Autism Spectrum Disorder (ASC) has widely gained the common attention from the public especially autistic communities. Individuals with ASC are said to have poor verbal skills and this affects them in carrying out their daily basis which they are afraid to expose themselves to the world due to their problems. ASC is diagnosed among children ranging from ages 5-12 years old and they suffer from the abnormal functioning of the brain which in turn causes lack of development activities. Thus, studies have shown that diagrammatic approaches help children with ASC to overcome their issues and improvise their visual and verbal skills. Picture Exchange Communication System or PECS consists of a series of illustrated cards and each cards has its own illustration with a caption on it. These children will understand the cards and they can compile several other cards to form sentences. This paper presents a mobile application called the Prospect, which has been developed using the agile development model for digital representation of PECS. The application is hoped to enhance the learning process and a better yielding results. © Published under licence by IOP Publishing Ltd.}, note = {cited By 0}, keywords = {Agile Development, Autism Spectrum Disorders, Brain, Development Activity, Digital Representations, Diseases, Education, Instant Messaging, Learning, Mobile Applications, Verbal Communication}, pubstate = {published}, tppubtype = {conference} } Autism Spectrum Disorder (ASC) has widely gained the common attention from the public especially autistic communities. Individuals with ASC are said to have poor verbal skills and this affects them in carrying out their daily basis which they are afraid to expose themselves to the world due to their problems. ASC is diagnosed among children ranging from ages 5-12 years old and they suffer from the abnormal functioning of the brain which in turn causes lack of development activities. Thus, studies have shown that diagrammatic approaches help children with ASC to overcome their issues and improvise their visual and verbal skills. Picture Exchange Communication System or PECS consists of a series of illustrated cards and each cards has its own illustration with a caption on it. These children will understand the cards and they can compile several other cards to form sentences. This paper presents a mobile application called the Prospect, which has been developed using the agile development model for digital representation of PECS. The application is hoped to enhance the learning process and a better yielding results. © Published under licence by IOP Publishing Ltd. |
Hasan, C Z C; Jailani, R; Tahir, Md N Use of statistical approaches and artificial neural networks to identify gait deviations in children with autism spectrum disorder Journal Article International Journal of Biology and Biomedical Engineering, 11 , pp. 74-79, 2017, ISSN: 19984510, (cited By 1). Abstract | Links | BibTeX | Tags: Article, Artificial Neural Network, Autism, Body Height, Body Mass, Children, Clinical Article, Controlled Study, Discriminant Analysis, Early Diagnosis, Female, Gait, Gait Analysis, Gait Disorder, Human, Learning, Male, Pediatrics, School Child, Statistical Analysis, Statistics, Time Series Analysis @article{Hasan201774, title = {Use of statistical approaches and artificial neural networks to identify gait deviations in children with autism spectrum disorder}, author = {C Z C Hasan and R Jailani and N Md Tahir}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85043500605&partnerID=40&md5=6f2ffe7c2f5daf9fd02d4456acb94438}, issn = {19984510}, year = {2017}, date = {2017-01-01}, journal = {International Journal of Biology and Biomedical Engineering}, volume = {11}, pages = {74-79}, publisher = {North Atlantic University Union NAUN}, abstract = {Automated differentiation of ASD gait from normal gait patterns is important for early diagnosis as well as ensuring rapid quantitative clinical decision and appropriate treatment planning. This study explores the use of statistical feature selection approaches and artificial neural networks (ANN) for automated identification of gait deviations in children with ASD, on the basis of dominant gait features derived from the three-dimensional (3D) joint kinematic data. The gait data from 30 ASD children and 30 normal healthy children were measured using a state-of-the-art 3D motion analysis system during self-selected speed barefoot walking. Kinematic gait features from the sagittal, frontal and transverse joint angles waveforms at the pelvis, hip, knee, and ankle were extracted using time-series parameterization. Two statistical feature selection techniques, namely the between-group tests (independent samples t-test and Mann-Whitney U test) and the stepwise discriminant analysis (SWDA) were adopted as feature selector to select the meaningful gait features that were then used to train the ANN. The 10-fold cross-validation test results indicate that the selected gait features using SWDA technique are more reliable for ASD gait classification with 91.7% accuracy, 93.3% sensitivity, and 90.0% specificity. The findings of the current study demonstrate that kinematic gait features with the combination of SWDA feature selector and ANN classifier would serve as a potential tool for early diagnosis of gait deviations in children with ASD as well as provide support to clinicians and therapists for making objective, accurate, and rapid clinical decisions that lead to the appropriate targeted treatments. © 2017 North Atlantic University Union NAUN. All Rights Reserved.}, note = {cited By 1}, keywords = {Article, Artificial Neural Network, Autism, Body Height, Body Mass, Children, Clinical Article, Controlled Study, Discriminant Analysis, Early Diagnosis, Female, Gait, Gait Analysis, Gait Disorder, Human, Learning, Male, Pediatrics, School Child, Statistical Analysis, Statistics, Time Series Analysis}, pubstate = {published}, tppubtype = {article} } Automated differentiation of ASD gait from normal gait patterns is important for early diagnosis as well as ensuring rapid quantitative clinical decision and appropriate treatment planning. This study explores the use of statistical feature selection approaches and artificial neural networks (ANN) for automated identification of gait deviations in children with ASD, on the basis of dominant gait features derived from the three-dimensional (3D) joint kinematic data. The gait data from 30 ASD children and 30 normal healthy children were measured using a state-of-the-art 3D motion analysis system during self-selected speed barefoot walking. Kinematic gait features from the sagittal, frontal and transverse joint angles waveforms at the pelvis, hip, knee, and ankle were extracted using time-series parameterization. Two statistical feature selection techniques, namely the between-group tests (independent samples t-test and Mann-Whitney U test) and the stepwise discriminant analysis (SWDA) were adopted as feature selector to select the meaningful gait features that were then used to train the ANN. The 10-fold cross-validation test results indicate that the selected gait features using SWDA technique are more reliable for ASD gait classification with 91.7% accuracy, 93.3% sensitivity, and 90.0% specificity. The findings of the current study demonstrate that kinematic gait features with the combination of SWDA feature selector and ANN classifier would serve as a potential tool for early diagnosis of gait deviations in children with ASD as well as provide support to clinicians and therapists for making objective, accurate, and rapid clinical decisions that lead to the appropriate targeted treatments. © 2017 North Atlantic University Union NAUN. All Rights Reserved. |
2016 |
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. |
Gravier, A; Quek, C; Duch, W; Wahab, A; Gravier-Rymaszewska, J Neural network modelling of the influence of channelopathies on reflex visual attention Journal Article Cognitive Neurodynamics, 10 (1), pp. 49-72, 2016, ISSN: 18714080, (cited By 8). Abstract | Links | BibTeX | Tags: Article, Artificial Neural Network, Attention, Autism, Calcium Channelopathy, Cell Structure, Cognition, Connectome, Electric Activity, Learning, Mathematical Analysis, Mathematical Model, Nerve Cell, Simulation, Visual Reflex @article{Gravier201649, title = {Neural network modelling of the influence of channelopathies on reflex visual attention}, author = {A Gravier and C Quek and W Duch and A Wahab and J Gravier-Rymaszewska}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84955207541&doi=10.1007%2fs11571-015-9365-x&partnerID=40&md5=52f56b25f1d05a2d8eb0249e67e49f45}, doi = {10.1007/s11571-015-9365-x}, issn = {18714080}, year = {2016}, date = {2016-01-01}, journal = {Cognitive Neurodynamics}, volume = {10}, number = {1}, pages = {49-72}, publisher = {Springer Netherlands}, abstract = {This paper introduces a model of Emergent Visual Attention in presence of calcium channelopathy (EVAC). By modelling channelopathy, EVAC constitutes an effort towards identifying the possible causes of autism. The network structure embodies the dual pathways model of cortical processing of visual input, with reflex attention as an emergent property of neural interactions. EVAC extends existing work by introducing attention shift in a larger-scale network and applying a phenomenological model of channelopathy. In presence of a distractor, the channelopathic network’s rate of failure to shift attention is lower than the control network’s, but overall, the control network exhibits a lower classification error rate. The simulation results also show differences in task-relative reaction times between control and channelopathic networks. The attention shift timings inferred from the model are consistent with studies of attention shift in autistic children. © 2015, Springer Science+Business Media Dordrecht.}, note = {cited By 8}, keywords = {Article, Artificial Neural Network, Attention, Autism, Calcium Channelopathy, Cell Structure, Cognition, Connectome, Electric Activity, Learning, Mathematical Analysis, Mathematical Model, Nerve Cell, Simulation, Visual Reflex}, pubstate = {published}, tppubtype = {article} } This paper introduces a model of Emergent Visual Attention in presence of calcium channelopathy (EVAC). By modelling channelopathy, EVAC constitutes an effort towards identifying the possible causes of autism. The network structure embodies the dual pathways model of cortical processing of visual input, with reflex attention as an emergent property of neural interactions. EVAC extends existing work by introducing attention shift in a larger-scale network and applying a phenomenological model of channelopathy. In presence of a distractor, the channelopathic network’s rate of failure to shift attention is lower than the control network’s, but overall, the control network exhibits a lower classification error rate. The simulation results also show differences in task-relative reaction times between control and channelopathic networks. The attention shift timings inferred from the model are consistent with studies of attention shift in autistic children. © 2015, Springer Science+Business Media Dordrecht. |
Aziz, N S A; Ahmad, W F W Proposed conceptual model of mobile numerical application for children with autism Conference Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781479978946, (cited By 3). Abstract | Links | BibTeX | Tags: Autism, Computation Theory, Conceptual Model, Diseases, Education, Learning, Mobile Applications, Statistics, Students @conference{Aziz201699, title = {Proposed conceptual model of mobile numerical application for children with autism}, author = {N S A Aziz and W F W Ahmad}, editor = {Aziz Jaafar Arshad Rahim I A J N I B S K N A Abdullah M.N. Ariff M.I.B.M.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995543505&doi=10.1109%2fISMSC.2015.7594035&partnerID=40&md5=5fb8809b855fbcb1904d50c6ec0646b2}, doi = {10.1109/ISMSC.2015.7594035}, isbn = {9781479978946}, year = {2016}, date = {2016-01-01}, journal = {2015 International Symposium on Mathematical Sciences and Computing Research, iSMSC 2015 - Proceedings}, pages = {99-103}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {Basic literacy and numeracy proficiency are two important skills which prepare and shape students for lifelong learning. This study focuses on numeracy skills for children with autism. It is crucial to conduct this study due to the increasing number of children with autism based on statistics data from the Malaysia Social Welfare Department. Children with autism have a neurological disorder that affects the functioning of the brain and causes problems with thinking, feeling, and language. Thus, a lot of studies have been conducted related to the social and literacy skills of the children with autism. However, numeracy skills are also important to the children and the advancement in mobile technology creates new methods to equip the children with numeracy skills. In order to develop a mobile numerical application that is able to fulfil the needs of these children, a proposed conceptual model will be constructed. The proposed conceptual model consists of learning theories, learning principles, multimedia elements together with colour psychology, number skills, language, gestures and contents. © 2015 IEEE.}, note = {cited By 3}, keywords = {Autism, Computation Theory, Conceptual Model, Diseases, Education, Learning, Mobile Applications, Statistics, Students}, pubstate = {published}, tppubtype = {conference} } Basic literacy and numeracy proficiency are two important skills which prepare and shape students for lifelong learning. This study focuses on numeracy skills for children with autism. It is crucial to conduct this study due to the increasing number of children with autism based on statistics data from the Malaysia Social Welfare Department. Children with autism have a neurological disorder that affects the functioning of the brain and causes problems with thinking, feeling, and language. Thus, a lot of studies have been conducted related to the social and literacy skills of the children with autism. However, numeracy skills are also important to the children and the advancement in mobile technology creates new methods to equip the children with numeracy skills. In order to develop a mobile numerical application that is able to fulfil the needs of these children, a proposed conceptual model will be constructed. The proposed conceptual model consists of learning theories, learning principles, multimedia elements together with colour psychology, number skills, language, gestures and contents. © 2015 IEEE. |
Azahari, I N N A; Ahmad, W F W; Jamaludin, Z; Hashim, A S The design of mobile social application for children with autism Conference Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781509051342, (cited By 3). Abstract | Links | BibTeX | Tags: Autism Spectrum Disorders, Children with Autism, Diseases, Education, Emotion, Heuristic Evaluation, Information Science, Interaction Skills, Learning, Mobile Applications, Mobile Computing, Social Aspect, Social Networking, Social Sciences, Social Skills, Teaching, User Interfaces @conference{Azahari2016547, title = {The design of mobile social application for children with autism}, author = {I N N A Azahari and W F W Ahmad and Z Jamaludin and A S Hashim}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010289959&doi=10.1109%2fICCOINS.2016.7783274&partnerID=40&md5=01592bfdb74208829ff0599447ad9e42}, doi = {10.1109/ICCOINS.2016.7783274}, isbn = {9781509051342}, year = {2016}, date = {2016-01-01}, journal = {2016 3rd International Conference on Computer and Information Sciences, ICCOINS 2016 - Proceedings}, pages = {547-552}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {Autism is a neural syndrome that complicates the growth of mind, producing challenging result in communicating, social interaction, and impairment in behaviour. Since there is no cure for autism, prompt interventions and effective educational exercises allow children to achieve massive improvement. During the teaching and learning process, children with autism require particular consideration and attention. Thus, with the implementation of information technology in special education, the teaching and learning process could to become more efficient. Struggle in social interaction skill is known as one of the main drawback encountered by children with autism. Therefore, a mobile social application is proposed to help the children to develop social interaction skills. Nonetheless, this paper only deliberates on the design phase mobile application development. It is developed for children with medium functioning Autism Spectrum Disorder (ASD) who are learning basic interaction skills. The application's design phase implements the results from the analysis phase, which has concluded earlier. Five evaluators were involved in the heuristic evaluation, in order to enhance the user interface of the mobile social application. The outcomes from the evaluation conclude that all evaluators has agreed with all heuristics. Not to mention, beneficial recommendations were also achieved from the evaluation. The future work of this paper will be the development phase of the mobile social application. © 2016 IEEE.}, note = {cited By 3}, keywords = {Autism Spectrum Disorders, Children with Autism, Diseases, Education, Emotion, Heuristic Evaluation, Information Science, Interaction Skills, Learning, Mobile Applications, Mobile Computing, Social Aspect, Social Networking, Social Sciences, Social Skills, Teaching, User Interfaces}, pubstate = {published}, tppubtype = {conference} } Autism is a neural syndrome that complicates the growth of mind, producing challenging result in communicating, social interaction, and impairment in behaviour. Since there is no cure for autism, prompt interventions and effective educational exercises allow children to achieve massive improvement. During the teaching and learning process, children with autism require particular consideration and attention. Thus, with the implementation of information technology in special education, the teaching and learning process could to become more efficient. Struggle in social interaction skill is known as one of the main drawback encountered by children with autism. Therefore, a mobile social application is proposed to help the children to develop social interaction skills. Nonetheless, this paper only deliberates on the design phase mobile application development. It is developed for children with medium functioning Autism Spectrum Disorder (ASD) who are learning basic interaction skills. The application's design phase implements the results from the analysis phase, which has concluded earlier. Five evaluators were involved in the heuristic evaluation, in order to enhance the user interface of the mobile social application. The outcomes from the evaluation conclude that all evaluators has agreed with all heuristics. Not to mention, beneficial recommendations were also achieved from the evaluation. The future work of this paper will be the development phase of the mobile social application. © 2016 IEEE. |
2015 |
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. |
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. |
Abdullah, M H L; Brereton, M Association for Computing Machinery, Inc, 2015, ISBN: 9781450336734, (cited By 10). Abstract | Links | BibTeX | Tags: Autism Spectrum Disorders, Children, Children with Autism, Communication, Diseases, Education, Human Computer Interaction, iPad Applications, Learning, MyCalendar, Participatory Design, Special Education, Teaching, Visual Languages @conference{Abdullah20151, title = {MyCalendar: Fostering communication for children with autism spectrum disorder through photos and videos}, author = {M H L Abdullah and M Brereton}, editor = {Smith Vetere Ploderer W F B Carter M. Gibbs M.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84963544904&doi=10.1145%2f2838739.2838785&partnerID=40&md5=1d0388dc4eb2a559796a0c8cf61f0e31}, doi = {10.1145/2838739.2838785}, isbn = {9781450336734}, year = {2015}, date = {2015-01-01}, journal = {OzCHI 2015: Being Human - Conference Proceedings}, pages = {1-9}, publisher = {Association for Computing Machinery, Inc}, abstract = {This paper presents MyCalendar; a visual calendar prototype App that was developed to support children with Autism Spectrum Disorder and language delays to communicate about their own activities and interests across the settings of home and school. MyCalendar was developed following in-depth fieldwork and participatory design sessions with parents, teachers and children from Preparatory year to year 2 of an Australian Primary School Special Education Unit catering largely for children with Autism Spectrum Disorder (ASD). Typically, children with ASD face difficulties in participating at school. MyCalendar was then evaluated over six months with four teachers, ten parents and eleven children. The study resulted in two key findings: (1) MyCalendar supported children who have ASD and limited verbal skills to better communicate their daily personal activities through photos and videos, encouraged by teachers and parents. (2) This deeper understanding of the children's daily lives enabled teachers to successfully model positive behaviours and to scaffold more relevant and meaningful learning opportunities by relating them to the children's lives. While it was initially expected that the activities would better support communication between teachers and parents, the MyCalendar led in fact to novel scaffolding of learning opportunities and modeling of communication in the classroom. Copyright © 2015 ACM.}, note = {cited By 10}, keywords = {Autism Spectrum Disorders, Children, Children with Autism, Communication, Diseases, Education, Human Computer Interaction, iPad Applications, Learning, MyCalendar, Participatory Design, Special Education, Teaching, Visual Languages}, pubstate = {published}, tppubtype = {conference} } This paper presents MyCalendar; a visual calendar prototype App that was developed to support children with Autism Spectrum Disorder and language delays to communicate about their own activities and interests across the settings of home and school. MyCalendar was developed following in-depth fieldwork and participatory design sessions with parents, teachers and children from Preparatory year to year 2 of an Australian Primary School Special Education Unit catering largely for children with Autism Spectrum Disorder (ASD). Typically, children with ASD face difficulties in participating at school. MyCalendar was then evaluated over six months with four teachers, ten parents and eleven children. The study resulted in two key findings: (1) MyCalendar supported children who have ASD and limited verbal skills to better communicate their daily personal activities through photos and videos, encouraged by teachers and parents. (2) This deeper understanding of the children's daily lives enabled teachers to successfully model positive behaviours and to scaffold more relevant and meaningful learning opportunities by relating them to the children's lives. While it was initially expected that the activities would better support communication between teachers and parents, the MyCalendar led in fact to novel scaffolding of learning opportunities and modeling of communication in the classroom. Copyright © 2015 ACM. |
Shamsuddin, S; Yussof, H; Hanapiah, F A; Mohamed, S; Jamil, N F F; Yunus, F W Robot-Assisted learning for communication-care in autism intervention Conference 2015-September , IEEE Computer Society, 2015, ISSN: 19457898, (cited By 5). Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, Autism Spectrum Disorders, Children with Autism, Communication Skills, Computer Aided Instruction, Diseases, Education, Educational Settings, Human Robot Interaction, Humanoid Robot, Learning, Robotics, Robots, Specific Interaction, Teaching @conference{Shamsuddin2015822, title = {Robot-Assisted learning for communication-care in autism intervention}, author = {S Shamsuddin and H Yussof and F A Hanapiah and S Mohamed and N F F Jamil and F W Yunus}, editor = {Campolo D Braun D. Yu H.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946072425&doi=10.1109%2fICORR.2015.7281304&partnerID=40&md5=3048519732d8127b2307d17a12e46463}, doi = {10.1109/ICORR.2015.7281304}, issn = {19457898}, year = {2015}, date = {2015-01-01}, journal = {IEEE International Conference on Rehabilitation Robotics}, volume = {2015-September}, pages = {822-827}, publisher = {IEEE Computer Society}, abstract = {Robot-based intervention for children with autism is an evolving research niche in human-robot interaction (HRI). Recent studies have covered the role of robots in clinical and experimental setting but not much on integrating them in educational setting. Our previous work had shown that interaction with a robot poses no adverse effects and that the robot's specific interaction scenarios were associated with less autistic behavior. Extending this impact on school-going children, interactions that are in-Tune with special education lessons are needed. This study aims to propose the integration of a robot into current learning environment for children with special needs, specifically autism. Six interaction scenarios had been designed based on the existing syllabus to teach communication skills, using the Applied Behavior Analysis (ABA) technique as the framework. Development of the robotic experience for learning also covers the required set-up involving participation from teachers. The actual research conduct involving school children, teachers and robot shall take place in the next phase. © 2015 IEEE.}, note = {cited By 5}, keywords = {Anthropomorphic Robots, Autism Spectrum Disorders, Children with Autism, Communication Skills, Computer Aided Instruction, Diseases, Education, Educational Settings, Human Robot Interaction, Humanoid Robot, Learning, Robotics, Robots, Specific Interaction, Teaching}, pubstate = {published}, tppubtype = {conference} } Robot-based intervention for children with autism is an evolving research niche in human-robot interaction (HRI). Recent studies have covered the role of robots in clinical and experimental setting but not much on integrating them in educational setting. Our previous work had shown that interaction with a robot poses no adverse effects and that the robot's specific interaction scenarios were associated with less autistic behavior. Extending this impact on school-going children, interactions that are in-Tune with special education lessons are needed. This study aims to propose the integration of a robot into current learning environment for children with special needs, specifically autism. Six interaction scenarios had been designed based on the existing syllabus to teach communication skills, using the Applied Behavior Analysis (ABA) technique as the framework. Development of the robotic experience for learning also covers the required set-up involving participation from teachers. The actual research conduct involving school children, teachers and robot shall take place in the next phase. © 2015 IEEE. |
Banire, B; Jomhari, N; Ahmad, R Visual Hybrid Development Learning System (VHDLS) Framework for Children with Autism Journal Article Journal of Autism and Developmental Disorders, 45 (10), pp. 3069-3084, 2015, ISSN: 01623257, (cited By 7). Abstract | Links | BibTeX | Tags: Article, Attention, Autism, Autism Spectrum Disorders, Children, Computer Interface, Education, Education of Intellectually Disabled, Educational Model, Feedback System, Female, Human, Learning, Male, Models, Occupational Therapist, Preschool, Preschool Child, Priority Journal, Procedures, Psychology, Quality of Life, Treatment Duration, User Interfaces, Visual Hybrid Development Learning System, Visual Stimulation @article{Banire20153069, title = {Visual Hybrid Development Learning System (VHDLS) Framework for Children with Autism}, author = {B Banire and N Jomhari and R Ahmad}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84941942795&doi=10.1007%2fs10803-015-2469-7&partnerID=40&md5=3c5ecc776725aea4e585e17a1ae805c7}, doi = {10.1007/s10803-015-2469-7}, issn = {01623257}, year = {2015}, date = {2015-01-01}, journal = {Journal of Autism and Developmental Disorders}, volume = {45}, number = {10}, pages = {3069-3084}, publisher = {Springer New York LLC}, abstract = {The effect of education on children with autism serves as a relative cure for their deficits. As a result of this, they require special techniques to gain their attention and interest in learning as compared to typical children. Several studies have shown that these children are visual learners. In this study, we proposed a Visual Hybrid Development Learning System (VHDLS) framework that is based on an instructional design model, multimedia cognitive learning theory, and learning style in order to guide software developers in developing learning systems for children with autism. The results from this study showed that the attention of children with autism increased more with the proposed VHDLS framework. © 2015, Springer Science+Business Media New York.}, note = {cited By 7}, keywords = {Article, Attention, Autism, Autism Spectrum Disorders, Children, Computer Interface, Education, Education of Intellectually Disabled, Educational Model, Feedback System, Female, Human, Learning, Male, Models, Occupational Therapist, Preschool, Preschool Child, Priority Journal, Procedures, Psychology, Quality of Life, Treatment Duration, User Interfaces, Visual Hybrid Development Learning System, Visual Stimulation}, pubstate = {published}, tppubtype = {article} } The effect of education on children with autism serves as a relative cure for their deficits. As a result of this, they require special techniques to gain their attention and interest in learning as compared to typical children. Several studies have shown that these children are visual learners. In this study, we proposed a Visual Hybrid Development Learning System (VHDLS) framework that is based on an instructional design model, multimedia cognitive learning theory, and learning style in order to guide software developers in developing learning systems for children with autism. The results from this study showed that the attention of children with autism increased more with the proposed VHDLS framework. © 2015, Springer Science+Business Media New York. |
2014 |
Kamaruzaman, M F; Azahari, M H H Form design development study on autistic counting skill learning application Conference Institute of Electrical and Electronics Engineers Inc., 2014, ISBN: 9781479945559, (cited By 10). Abstract | Links | BibTeX | Tags: Autistic Children, Children with Autism, Computer Aided Instruction, Counting Skill, Design Process, Diseases, Education, Embedded Technology, Engineering Education, Learning, Theoretical Framework, Touchscreens @conference{Kamaruzaman201470, title = {Form design development study on autistic counting skill learning application}, author = {M F Kamaruzaman and M H H Azahari}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925947367&doi=10.1109%2fI4CT.2014.6914148&partnerID=40&md5=60cc4a83e2af10b36fafacd86d05c6c3}, doi = {10.1109/I4CT.2014.6914148}, isbn = {9781479945559}, year = {2014}, date = {2014-01-01}, journal = {I4CT 2014 - 1st International Conference on Computer, Communications, and Control Technology, Proceedings}, pages = {70-74}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {Children with autism have their own set of impairments that affect their developments. Thus, the chance to attain self-determination may be critical for most if not all of autistic children. However, it is essential for them to obtain vital skill system in order to achieve a certain level of independent. Thus, it is necessary for every autistic children to acquire basic counting skills to enhance their self-determination. With the emergence of assistive learning technology such as Smartphone, PDA, tablets and laptop with touch screen facility, there are new certain ways to enrich the quality of life for individuals with autism. This study aims to explore the basic counting skills based dynamic visual for children with autism that will possibly be of assistance to parents, educators and facilitators in the development of digital assistive learning tools to meet the needs of autistic children's learning environment. From the proposed theoretical framework, an application was designed and tested on some of autistic users. Based on the observation of the experiment, the users showed positive attitude towards the outcome of the application. © 2014 IEEE.}, note = {cited By 10}, keywords = {Autistic Children, Children with Autism, Computer Aided Instruction, Counting Skill, Design Process, Diseases, Education, Embedded Technology, Engineering Education, Learning, Theoretical Framework, Touchscreens}, pubstate = {published}, tppubtype = {conference} } Children with autism have their own set of impairments that affect their developments. Thus, the chance to attain self-determination may be critical for most if not all of autistic children. However, it is essential for them to obtain vital skill system in order to achieve a certain level of independent. Thus, it is necessary for every autistic children to acquire basic counting skills to enhance their self-determination. With the emergence of assistive learning technology such as Smartphone, PDA, tablets and laptop with touch screen facility, there are new certain ways to enrich the quality of life for individuals with autism. This study aims to explore the basic counting skills based dynamic visual for children with autism that will possibly be of assistance to parents, educators and facilitators in the development of digital assistive learning tools to meet the needs of autistic children's learning environment. From the proposed theoretical framework, an application was designed and tested on some of autistic users. Based on the observation of the experiment, the users showed positive attitude towards the outcome of the application. © 2014 IEEE. |
Sudirman, R; Hussin, S S Sensory responses of autism via electroencephalography for Sensory Profile Conference Institute of Electrical and Electronics Engineers Inc., 2014, ISBN: 9781479956869, (cited By 3). Abstract | Links | BibTeX | Tags: Autism, Discrete Wavelet Transforms, Diseases, Electroencephalography, Electrophysiology, Independent Component Analysis, International System, Learning, Sensory Analysis, Sensory Profiles, Sensory Profiling, Sensory Stimulation, Signal Processing, Standard Deviation, Wavelet Packet Transforms @conference{Sudirman2014626, title = {Sensory responses of autism via electroencephalography for Sensory Profile}, author = {R Sudirman and S S Hussin}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946435600&doi=10.1109%2fICCSCE.2014.7072794&partnerID=40&md5=3e6f1cfe19eae4fad359d2493aebd7e0}, doi = {10.1109/ICCSCE.2014.7072794}, isbn = {9781479956869}, year = {2014}, date = {2014-01-01}, journal = {Proceedings - 4th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2014}, pages = {626-631}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {The aim of this study is to investigate the brain signals of autism children through electroencephalography (EEG) associated to physical tasks. The physical task was meant to stimulate the sensitivity correlation of sensory response of a child. A group of autism children was chosen for this study and were given by five sensory stimulations which are audio, taste, touch, visual and vestibular. The acquisition of brain signals was acquainted using EEG Neurofax 9200 and the electrode positions were using 10-20 International System placements. The preprocessing signals were analyzed using independent component analysis (ICA) using EEGLAB Software and Discrete Wavelet Transform (DWT). The alpha wave was selected by level 6 decomposition and the extracted features represents the characteristic of the sensory task. The means, standard deviations and approximation entropy were extracted on the clean signals and forms into Sensory Profile (Sensory Profiling). From the overall results, the behavior of each autism children has been observed unstable emotion while running the sensory stimulation. The observation also helps to improve their learning strategy for the future work in assessment. © 2014 IEEE.}, note = {cited By 3}, keywords = {Autism, Discrete Wavelet Transforms, Diseases, Electroencephalography, Electrophysiology, Independent Component Analysis, International System, Learning, Sensory Analysis, Sensory Profiles, Sensory Profiling, Sensory Stimulation, Signal Processing, Standard Deviation, Wavelet Packet Transforms}, pubstate = {published}, tppubtype = {conference} } The aim of this study is to investigate the brain signals of autism children through electroencephalography (EEG) associated to physical tasks. The physical task was meant to stimulate the sensitivity correlation of sensory response of a child. A group of autism children was chosen for this study and were given by five sensory stimulations which are audio, taste, touch, visual and vestibular. The acquisition of brain signals was acquainted using EEG Neurofax 9200 and the electrode positions were using 10-20 International System placements. The preprocessing signals were analyzed using independent component analysis (ICA) using EEGLAB Software and Discrete Wavelet Transform (DWT). The alpha wave was selected by level 6 decomposition and the extracted features represents the characteristic of the sensory task. The means, standard deviations and approximation entropy were extracted on the clean signals and forms into Sensory Profile (Sensory Profiling). From the overall results, the behavior of each autism children has been observed unstable emotion while running the sensory stimulation. The observation also helps to improve their learning strategy for the future work in assessment. © 2014 IEEE. |
2013 |
Khowaja, K; Salim, S S A systematic review of strategies and computer-based intervention (CBI) for reading comprehension of children with autism Journal Article Research in Autism Spectrum Disorders, 7 (9), pp. 1111-1121, 2013, ISSN: 17509467, (cited By 28). Abstract | Links | BibTeX | Tags: Attention, Autism, Bibliographic Database, Children, Clinical Effectiveness, Clinical Observation, Cognition, Comprehension, Computer Assisted Therapy, Computer Based Intervention, Explicit Memory, Human, Learning, Linguistics, Motivation, Multimedia, Pretest Posttest Design, Priority Journal, Reading, Reading Comprehension, Review, Systematic Review, Treatment Outcome @article{Khowaja20131111, title = {A systematic review of strategies and computer-based intervention (CBI) for reading comprehension of children with autism}, author = {K Khowaja and S S Salim}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84879609907&doi=10.1016%2fj.rasd.2013.05.009&partnerID=40&md5=6ba3e9315ee8b3cecb6248b97198313d}, doi = {10.1016/j.rasd.2013.05.009}, issn = {17509467}, year = {2013}, date = {2013-01-01}, journal = {Research in Autism Spectrum Disorders}, volume = {7}, number = {9}, pages = {1111-1121}, abstract = {This paper presents a systematic review of relevant published studies on reading comprehension for children with autism, focusing on vocabulary instruction and text comprehension instruction from years 2000 to 2011. This systematic review attempts to address three specific research questions: strategies of vocabulary instruction and text comprehension instruction used, computer-based intervention (CBI) used or developed during study, and the effectiveness of using CBI for teaching children with autism. There are five strategies of vocabulary instruction and seven strategies of text comprehension instruction. Results indicate that two strategies of vocabulary instruction, multimedia methods and explicit instruction were found to be more commonly used than the other three. On the same note, question answering strategy of text comprehension instruction was discovered to be used more often than the other six. Results also indicate that children with autism can benefit from the strategies of reading comprehension and that the use of CBI as a mode of instruction for reading comprehension improved learning of children. This is clearly evident judging from the performance of children between pre-tests and post-tests of studies in which CBI was used. However, due to heterogeneity of participants, this is not always the case; a few studies reported no improvement in the learning of children with autism. © 2013 Elsevier Ltd. Allrights reserved.}, note = {cited By 28}, keywords = {Attention, Autism, Bibliographic Database, Children, Clinical Effectiveness, Clinical Observation, Cognition, Comprehension, Computer Assisted Therapy, Computer Based Intervention, Explicit Memory, Human, Learning, Linguistics, Motivation, Multimedia, Pretest Posttest Design, Priority Journal, Reading, Reading Comprehension, Review, Systematic Review, Treatment Outcome}, pubstate = {published}, tppubtype = {article} } This paper presents a systematic review of relevant published studies on reading comprehension for children with autism, focusing on vocabulary instruction and text comprehension instruction from years 2000 to 2011. This systematic review attempts to address three specific research questions: strategies of vocabulary instruction and text comprehension instruction used, computer-based intervention (CBI) used or developed during study, and the effectiveness of using CBI for teaching children with autism. There are five strategies of vocabulary instruction and seven strategies of text comprehension instruction. Results indicate that two strategies of vocabulary instruction, multimedia methods and explicit instruction were found to be more commonly used than the other three. On the same note, question answering strategy of text comprehension instruction was discovered to be used more often than the other six. Results also indicate that children with autism can benefit from the strategies of reading comprehension and that the use of CBI as a mode of instruction for reading comprehension improved learning of children. This is clearly evident judging from the performance of children between pre-tests and post-tests of studies in which CBI was used. However, due to heterogeneity of participants, this is not always the case; a few studies reported no improvement in the learning of children with autism. © 2013 Elsevier Ltd. Allrights reserved. |
Hamid, A C; Miskam, M A; Yussof, H; Shamsuddin, S; Hashim, H; Ismail, L Human-robot interaction (HRI) for children with autism to augment communication skills Journal Article Applied Mechanics and Materials, 393 , pp. 598-603, 2013, ISSN: 16609336, (cited By 1). Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, Autism, Children with Autism, Communication, Communication Skills, Diseases, Education, Human Robot Interaction, Humanoid Robot, Humanoid Robot NAO, Intervention Programs, Learning, Man Machine Systems, Mechanical Engineering, Teaching, Two-Way Communications @article{Hamid2013598, title = {Human-robot interaction (HRI) for children with autism to augment communication skills}, author = {A C Hamid and M A Miskam and H Yussof and S Shamsuddin and H Hashim and L Ismail}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886245343&doi=10.4028%2fwww.scientific.net%2fAMM.393.598&partnerID=40&md5=a580bbcbd654ebb6c19b75fa27bdf75e}, doi = {10.4028/www.scientific.net/AMM.393.598}, issn = {16609336}, year = {2013}, date = {2013-01-01}, journal = {Applied Mechanics and Materials}, volume = {393}, pages = {598-603}, abstract = {This paper presents a case study of robot-based intervention program for children with autism. The study focuses on two-way communication between children with autism and a humanoid robot NAO. The aim of this study is to develop a set of teaching and learning modules on communication through question type conversation and song-based approach. Module developed in this study is programmed using NAO's choregraphe, being imbedded later on and perform action. Both children participating in this study can communicate verbally and have been diagnosed with mild autism. Response from this exposure shows that the human toddler-like robot can be used as a platform to augment and facilitate communication effectively with children with autism. © (2013) Trans Tech Publications, Switzerland.}, note = {cited By 1}, keywords = {Anthropomorphic Robots, Autism, Children with Autism, Communication, Communication Skills, Diseases, Education, Human Robot Interaction, Humanoid Robot, Humanoid Robot NAO, Intervention Programs, Learning, Man Machine Systems, Mechanical Engineering, Teaching, Two-Way Communications}, pubstate = {published}, tppubtype = {article} } This paper presents a case study of robot-based intervention program for children with autism. The study focuses on two-way communication between children with autism and a humanoid robot NAO. The aim of this study is to develop a set of teaching and learning modules on communication through question type conversation and song-based approach. Module developed in this study is programmed using NAO's choregraphe, being imbedded later on and perform action. Both children participating in this study can communicate verbally and have been diagnosed with mild autism. Response from this exposure shows that the human toddler-like robot can be used as a platform to augment and facilitate communication effectively with children with autism. © (2013) Trans Tech Publications, Switzerland. |
2012 |
Cheah, P -S; Ramshaw, H S; Thomas, P Q; Toyo-Oka, K; Xu, X; Martin, S; Coyle, P; Guthridge, M A; Stomski, F; Buuse, Van Den M; Wynshaw-Boris, A; Lopez, A F; Schwarz, Q P Neurodevelopmental and neuropsychiatric behaviour defects arise from 14-3-3ζ deficiency Journal Article Molecular Psychiatry, 17 (4), pp. 451-466, 2012, ISSN: 13594184, (cited By 58). Abstract | Links | BibTeX | Tags: 14-3-3 Proteins, Animal Experiment, Animal Model, Animal Tissue, Animals, Article, Autism, Behaviour Disorder, Bipolar Disorder, Brain, Cell Movement, Cells, Cognitive Defect, Controlled Study, Cultured, Disease Models, Disrupted in Schizophrenia 1 Protein, Embryo, Female, Gene, Gene Deletion, Genetic Predisposition to Disease, Glutamic Acid, Hippocampal Mossy Fiber, Hippocampus, Human, Hyperactivity, Inbred C57BL, Isoprotein, Knockout, Learning, Male, Maze Learning, Memory, Mice, Motor Activity, Mouse, Neurogenesis, Neuronal Migration Disorder, Neurons, Neuropsychiatry, Nonhuman, Priority Journal, Protein 14-3-3, Protein 14-3-3 Zeta, Protein Deficiency, Protein Interaction, Recognition, Risk Factor, Schizophrenia, Sensory Gating, Synapse, Unclassified Drug @article{Cheah2012451, title = {Neurodevelopmental and neuropsychiatric behaviour defects arise from 14-3-3ζ deficiency}, author = {P -S Cheah and H S Ramshaw and P Q Thomas and K Toyo-Oka and X Xu and S Martin and P Coyle and M A Guthridge and F Stomski and M Van Den Buuse and A Wynshaw-Boris and A F Lopez and Q P Schwarz}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84859007028&doi=10.1038%2fmp.2011.158&partnerID=40&md5=7f507fef31a192a10b3cde7bf69b5442}, doi = {10.1038/mp.2011.158}, issn = {13594184}, year = {2012}, date = {2012-01-01}, journal = {Molecular Psychiatry}, volume = {17}, number = {4}, pages = {451-466}, abstract = {Complex neuropsychiatric disorders are believed to arise from multiple synergistic deficiencies within connected biological networks controlling neuronal migration, axonal pathfinding and synapse formation. Here, we show that deletion of 14-3-3ζ causes neurodevelopmental anomalies similar to those seen in neuropsychiatric disorders such as schizophrenia, autism spectrum disorder and bipolar disorder. 14-3-3ζ-Deficient mice displayed striking behavioural and cognitive deficiencies including a reduced capacity to learn and remember, hyperactivity and disrupted sensorimotor gating. These deficits are accompanied by subtle developmental abnormalities of the hippocampus that are underpinned by aberrant neuronal migration. Significantly, 14-3-3ζ- deficient mice exhibited abnormal mossy fibre navigation and glutamatergic synapse formation. The molecular basis of these defects involves the schizophrenia risk factor, DISC1, which interacts isoform specifically with 14-3-3ζ. Our data provide the first evidence of a direct role for 14-3-3ζ deficiency in the aetiology of neurodevelopmental disorders and identifies 14-3-3ζ as a central risk factor in the schizophrenia protein interaction network. © 2012 Macmillan Publishers Limited All rights reserved.}, note = {cited By 58}, keywords = {14-3-3 Proteins, Animal Experiment, Animal Model, Animal Tissue, Animals, Article, Autism, Behaviour Disorder, Bipolar Disorder, Brain, Cell Movement, Cells, Cognitive Defect, Controlled Study, Cultured, Disease Models, Disrupted in Schizophrenia 1 Protein, Embryo, Female, Gene, Gene Deletion, Genetic Predisposition to Disease, Glutamic Acid, Hippocampal Mossy Fiber, Hippocampus, Human, Hyperactivity, Inbred C57BL, Isoprotein, Knockout, Learning, Male, Maze Learning, Memory, Mice, Motor Activity, Mouse, Neurogenesis, Neuronal Migration Disorder, Neurons, Neuropsychiatry, Nonhuman, Priority Journal, Protein 14-3-3, Protein 14-3-3 Zeta, Protein Deficiency, Protein Interaction, Recognition, Risk Factor, Schizophrenia, Sensory Gating, Synapse, Unclassified Drug}, pubstate = {published}, tppubtype = {article} } Complex neuropsychiatric disorders are believed to arise from multiple synergistic deficiencies within connected biological networks controlling neuronal migration, axonal pathfinding and synapse formation. Here, we show that deletion of 14-3-3ζ causes neurodevelopmental anomalies similar to those seen in neuropsychiatric disorders such as schizophrenia, autism spectrum disorder and bipolar disorder. 14-3-3ζ-Deficient mice displayed striking behavioural and cognitive deficiencies including a reduced capacity to learn and remember, hyperactivity and disrupted sensorimotor gating. These deficits are accompanied by subtle developmental abnormalities of the hippocampus that are underpinned by aberrant neuronal migration. Significantly, 14-3-3ζ- deficient mice exhibited abnormal mossy fibre navigation and glutamatergic synapse formation. The molecular basis of these defects involves the schizophrenia risk factor, DISC1, which interacts isoform specifically with 14-3-3ζ. Our data provide the first evidence of a direct role for 14-3-3ζ deficiency in the aetiology of neurodevelopmental disorders and identifies 14-3-3ζ as a central risk factor in the schizophrenia protein interaction network. © 2012 Macmillan Publishers Limited All rights reserved. |
2011 |
Dolah, Jasni; Yahaya, Wan Ahmad Jaafar Wan; Chong, Toh Seong THE IMPACT OF INFORMAL CONVERSATIONAL AND VISIBLE AUTHOR PRINCIPLE IN INCREASING AWARENESS OF AUTISM THROUGH MULTIMEDIA LEARNING Inproceedings Chova, LG; Torres, IC; Martinez, AL (Ed.): INTED2011: 5TH INTERNATIONAL TECHNOLOGY, EDUCATION AND DEVELOPMENT CONFERENCE, pp. 3637-3641, IATED-INT ASSOC TECHNOLOGY EDUCATION & DEVELOPMENT, LAURI VOLPI 6, VALENICA, BURJASSOT 46100, SPAIN, 2011, ISBN: 978-84-614-7423-3, (5th International Technology, Education and Development Conference (INTED), Valencia, SPAIN, MAR 07-09, 2011). Abstract | BibTeX | Tags: Author, Conversational, Informal, Learning, Multimedia, Visible @inproceedings{ISI:000326447703099, title = {THE IMPACT OF INFORMAL CONVERSATIONAL AND VISIBLE AUTHOR PRINCIPLE IN INCREASING AWARENESS OF AUTISM THROUGH MULTIMEDIA LEARNING}, author = {Jasni Dolah and Wan Ahmad Jaafar Wan Yahaya and Toh Seong Chong}, editor = {LG Chova and IC Torres and AL Martinez}, isbn = {978-84-614-7423-3}, year = {2011}, date = {2011-01-01}, booktitle = {INTED2011: 5TH INTERNATIONAL TECHNOLOGY, EDUCATION AND DEVELOPMENT CONFERENCE}, pages = {3637-3641}, publisher = {IATED-INT ASSOC TECHNOLOGY EDUCATION & DEVELOPMENT}, address = {LAURI VOLPI 6, VALENICA, BURJASSOT 46100, SPAIN}, abstract = {The purpose of this paper is to explain the impact of Informal Conversational and Visible Author principle in enhancing awareness of parents in learning autistic character through the use of Multimedia Learning. The main objective of this research is to increase the level of awareness amongst autistic parents especially on how to identify the early symptoms of autistic children. Based on these two principles, hopefully it could support and increase the level of cognitive load, awareness and motivation. The purpose of this alternative being introduced is to spark their awareness in identifying the early characteristic so that the autistic parent's can do an early prevention in identifying the autism symptoms. The selection of these principles was based on the literature review that relate to cognitive theories of learning which is human strive to make sense of presented material by applying appropriate cognitive process. Thus instruction should not only present information but also spark the suitable cognitive processing in the learner. The issues of this research were derived from the feedback received from the respondents through the Preliminary Investigation ( PI) that has been conducted earlier. The lack of knowledge of autism symptoms among society in Malaysia are the main issues that lead to this problem. The findings from this paper will help researcher to develop an Interactive Multimedia Learning Awareness (IMLA) tools so that it can help the parent's to use in identifying the early characteristic of autism children in future.}, note = {5th International Technology, Education and Development Conference (INTED), Valencia, SPAIN, MAR 07-09, 2011}, keywords = {Author, Conversational, Informal, Learning, Multimedia, Visible}, pubstate = {published}, tppubtype = {inproceedings} } The purpose of this paper is to explain the impact of Informal Conversational and Visible Author principle in enhancing awareness of parents in learning autistic character through the use of Multimedia Learning. The main objective of this research is to increase the level of awareness amongst autistic parents especially on how to identify the early symptoms of autistic children. Based on these two principles, hopefully it could support and increase the level of cognitive load, awareness and motivation. The purpose of this alternative being introduced is to spark their awareness in identifying the early characteristic so that the autistic parent's can do an early prevention in identifying the autism symptoms. The selection of these principles was based on the literature review that relate to cognitive theories of learning which is human strive to make sense of presented material by applying appropriate cognitive process. Thus instruction should not only present information but also spark the suitable cognitive processing in the learner. The issues of this research were derived from the feedback received from the respondents through the Preliminary Investigation ( PI) that has been conducted earlier. The lack of knowledge of autism symptoms among society in Malaysia are the main issues that lead to this problem. The findings from this paper will help researcher to develop an Interactive Multimedia Learning Awareness (IMLA) tools so that it can help the parent's to use in identifying the early characteristic of autism children in future. |
2009 |
Ismail, A; Omar, N; Zin, A M 1 , 2009, ISBN: 9781424449132, (cited By 12). Abstract | Links | BibTeX | Tags: Application Softwares, Autistic Children, Children with Autism, Communication Skills, Computer Software, Development Approach, Education, Educational Software, Electrical Engineering, End-users, Handicapped Persons, Learning, Learning Disorder, Personalizations, Software Design, Software Development, Software Development Methods @conference{Ismail2009299, title = {Developing learning software for children with learning disabilities through block-based development approach}, author = {A Ismail and N Omar and A M Zin}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-70449731050&doi=10.1109%2fICEEI.2009.5254772&partnerID=40&md5=20affae3e6e2e65aeb077b0827ec63f1}, doi = {10.1109/ICEEI.2009.5254772}, isbn = {9781424449132}, year = {2009}, date = {2009-01-01}, journal = {Proceedings of the 2009 International Conference on Electrical Engineering and Informatics, ICEEI 2009}, volume = {1}, pages = {299-303}, abstract = {Children with learning disability such as autism who have serious impairments with social, emotional, and communication skills require a high degree of personalization in using the educational software develop for them. The aim of this paper is to propose Block-Based Software Development method and approach that enables the end-users (such as parents and teachers) to build application software to suit the different need of an autistic child. This research hopefully can produce useful tailorable learning software in order to assist educating autistic children. © 2009 IEEE.}, note = {cited By 12}, keywords = {Application Softwares, Autistic Children, Children with Autism, Communication Skills, Computer Software, Development Approach, Education, Educational Software, Electrical Engineering, End-users, Handicapped Persons, Learning, Learning Disorder, Personalizations, Software Design, Software Development, Software Development Methods}, pubstate = {published}, tppubtype = {conference} } Children with learning disability such as autism who have serious impairments with social, emotional, and communication skills require a high degree of personalization in using the educational software develop for them. The aim of this paper is to propose Block-Based Software Development method and approach that enables the end-users (such as parents and teachers) to build application software to suit the different need of an autistic child. This research hopefully can produce useful tailorable learning software in order to assist educating autistic children. © 2009 IEEE. |
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2020 |
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 |
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). |
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 |
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). |
Improved binary dragonfly optimization algorithm and wavelet packet based non-linear features for infant cry classification Journal Article Computer Methods and Programs in Biomedicine, 155 , pp. 39-51, 2018, ISSN: 01692607, (cited By 21). |
2017 |
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). |
Emotional regulation in autism spectrum disorders: A new proposed model for regulating emotions through parent education Journal Article Journal of Global Pharma Technology, 9 (7), pp. 32-43, 2017, ISSN: 09758542, (cited By 0). |
Institute of Electrical and Electronics Engineers Inc., 2017, ISBN: 9781509009251, (cited By 0). |
226 (1), Institute of Physics Publishing, 2017, ISSN: 17578981, (cited By 0). |
Use of statistical approaches and artificial neural networks to identify gait deviations in children with autism spectrum disorder Journal Article International Journal of Biology and Biomedical Engineering, 11 , pp. 74-79, 2017, ISSN: 19984510, (cited By 1). |
2016 |
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). |
Neural network modelling of the influence of channelopathies on reflex visual attention Journal Article Cognitive Neurodynamics, 10 (1), pp. 49-72, 2016, ISSN: 18714080, (cited By 8). |
Proposed conceptual model of mobile numerical application for children with autism Conference Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781479978946, (cited By 3). |
The design of mobile social application for children with autism Conference Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781509051342, (cited By 3). |
2015 |
AUTISTHERAPIBOT: Autonomous robotic autism therapists assistant for autistic children Conference Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479957651, (cited By 1). |
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). |
Association for Computing Machinery, Inc, 2015, ISBN: 9781450336734, (cited By 10). |
Robot-Assisted learning for communication-care in autism intervention Conference 2015-September , IEEE Computer Society, 2015, ISSN: 19457898, (cited By 5). |
Visual Hybrid Development Learning System (VHDLS) Framework for Children with Autism Journal Article Journal of Autism and Developmental Disorders, 45 (10), pp. 3069-3084, 2015, ISSN: 01623257, (cited By 7). |
2014 |
Form design development study on autistic counting skill learning application Conference Institute of Electrical and Electronics Engineers Inc., 2014, ISBN: 9781479945559, (cited By 10). |
Sensory responses of autism via electroencephalography for Sensory Profile Conference Institute of Electrical and Electronics Engineers Inc., 2014, ISBN: 9781479956869, (cited By 3). |
2013 |
A systematic review of strategies and computer-based intervention (CBI) for reading comprehension of children with autism Journal Article Research in Autism Spectrum Disorders, 7 (9), pp. 1111-1121, 2013, ISSN: 17509467, (cited By 28). |
Human-robot interaction (HRI) for children with autism to augment communication skills Journal Article Applied Mechanics and Materials, 393 , pp. 598-603, 2013, ISSN: 16609336, (cited By 1). |
2012 |
Neurodevelopmental and neuropsychiatric behaviour defects arise from 14-3-3ζ deficiency Journal Article Molecular Psychiatry, 17 (4), pp. 451-466, 2012, ISSN: 13594184, (cited By 58). |
2011 |
THE IMPACT OF INFORMAL CONVERSATIONAL AND VISIBLE AUTHOR PRINCIPLE IN INCREASING AWARENESS OF AUTISM THROUGH MULTIMEDIA LEARNING Inproceedings Chova, LG; Torres, IC; Martinez, AL (Ed.): INTED2011: 5TH INTERNATIONAL TECHNOLOGY, EDUCATION AND DEVELOPMENT CONFERENCE, pp. 3637-3641, IATED-INT ASSOC TECHNOLOGY EDUCATION & DEVELOPMENT, LAURI VOLPI 6, VALENICA, BURJASSOT 46100, SPAIN, 2011, ISBN: 978-84-614-7423-3, (5th International Technology, Education and Development Conference (INTED), Valencia, SPAIN, MAR 07-09, 2011). |
2009 |
1 , 2009, ISBN: 9781424449132, (cited By 12). |