2017 |
Abdullah, M H L; Brereton, M MyCalendar: Supporting children on the autism spectrum to learn language and appropriate behaviour Conference Association for Computing Machinery, 2017, ISBN: 9781450353793, (cited By 1). Abstract | Links | BibTeX | Tags: Autism Spectrum Disorders, Behaviour, Children, Communication, Diseases, Human Computer Interaction, Interactive Computer Systems, iPad Applications, Language, MyCalendar, Photo and Video, Socialisation, Teaching @conference{Abdullah2017201, title = {MyCalendar: Supporting children on the autism spectrum to learn language and appropriate behaviour}, author = {M H L Abdullah and M Brereton}, editor = {Soro Ploderer Waycott Morrison A B J A Brereton M. Vyas D.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044237930&doi=10.1145%2f3152771.3152793&partnerID=40&md5=eebe825991d9c6b91971c67113c9b100}, doi = {10.1145/3152771.3152793}, isbn = {9781450353793}, year = {2017}, date = {2017-01-01}, journal = {ACM International Conference Proceeding Series}, pages = {201-209}, publisher = {Association for Computing Machinery}, abstract = {This paper1 presents a study in which a mobile visual calendar application, 'MyCalendar' was used to try to support communication and interaction of children with Autism Spectrum Disorder. This paper reports findings on how the App was used in school classrooms. MyCalendar was evaluated with 11 children in an Australian Autism Special Education Unit over six months and was found to stimulate excitement with video and photo sharing as well as interaction in specific classroom activities. Our previous work examined interactions between home and school, and interactions at home supported by MyCalendar. This analysis focuses entirely on interactions at school by examining data from classroom activities. Three findings revealed: (1) the MyCalendar application supports learning activities in the classroom and facilitates the inclusion of children with ASD who have limited verbal skills. The sharing of each child's personal experience enabled the teachers and children to form a common basis for communication and adding vocabulary, as well as allowing the teacher to model language so as to identify children's emotions; (2) MyCalendar allowed children with limited verbal skills to better communicate their real interests through photos and videos. This enabled the teacher to better identify each child's interest and thereby scaffold more relevant and meaningful learning; (3) Understanding interests enabled teachers to successfully motivate children to interact more in formal learning activities. While it was initially expected the activities would better support communication between teacher and children, the larger and unanticipated effect has been to create opportunities for structuring and scaffolding communication and social interaction in the classroom. © 2017 Association for Computing Machinery. All rights reserved.}, note = {cited By 1}, keywords = {Autism Spectrum Disorders, Behaviour, Children, Communication, Diseases, Human Computer Interaction, Interactive Computer Systems, iPad Applications, Language, MyCalendar, Photo and Video, Socialisation, Teaching}, pubstate = {published}, tppubtype = {conference} } This paper1 presents a study in which a mobile visual calendar application, 'MyCalendar' was used to try to support communication and interaction of children with Autism Spectrum Disorder. This paper reports findings on how the App was used in school classrooms. MyCalendar was evaluated with 11 children in an Australian Autism Special Education Unit over six months and was found to stimulate excitement with video and photo sharing as well as interaction in specific classroom activities. Our previous work examined interactions between home and school, and interactions at home supported by MyCalendar. This analysis focuses entirely on interactions at school by examining data from classroom activities. Three findings revealed: (1) the MyCalendar application supports learning activities in the classroom and facilitates the inclusion of children with ASD who have limited verbal skills. The sharing of each child's personal experience enabled the teachers and children to form a common basis for communication and adding vocabulary, as well as allowing the teacher to model language so as to identify children's emotions; (2) MyCalendar allowed children with limited verbal skills to better communicate their real interests through photos and videos. This enabled the teacher to better identify each child's interest and thereby scaffold more relevant and meaningful learning; (3) Understanding interests enabled teachers to successfully motivate children to interact more in formal learning activities. While it was initially expected the activities would better support communication between teacher and children, the larger and unanticipated effect has been to create opportunities for structuring and scaffolding communication and social interaction in the classroom. © 2017 Association for Computing Machinery. All rights reserved. |
2016 |
Abdullah, M H L; Wilson, C; Brereton, M MyCalendar: Supporting families to communicate with their child on the autism spectrum Conference Association for Computing Machinery, Inc, 2016, ISBN: 9781450346184, (cited By 4). Abstract | Links | BibTeX | Tags: Autism Spectrum Disorders, Behaviour, Children, Communication, Diseases, Human Computer Interaction, Interactive Computer Systems, iPad Applications, MyCalendar, Photo and Video, Socialisation @conference{Abdullah2016613, title = {MyCalendar: Supporting families to communicate with their child on the autism spectrum}, author = {M H L Abdullah and C Wilson and M Brereton}, editor = {Parker C.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85012023591&doi=10.1145%2f3010915.3011000&partnerID=40&md5=1b5c49a1a74b95fd3e456bc1ea1d9ee4}, doi = {10.1145/3010915.3011000}, isbn = {9781450346184}, year = {2016}, date = {2016-01-01}, journal = {Proceedings of the 28th Australian Computer-Human Interaction Conference, OzCHI 2016}, pages = {613-617}, publisher = {Association for Computing Machinery, Inc}, abstract = {This paper presents a study in which a mobile application, 'MyCalendar', was trialled with children on the autism spectrum and their families. In previous work, we described how the MyCalendar app supported communication across both home and school settings through photos and videos of the child's activities, presented in the format of a visual calendar. These visuals supported the child to communicate and socialise and to recall activities and helped adults to better understand the child holistically. This note augments previous work on MyCalendar by focusing on interactions at home within the family. Findings revealed that routine review of activities documented in MyCalendar enabled children to participate more in family conversations, extended their time spent interacting socially, and reinforced social relationships. This gave the children on the autism spectrum greater opportunity to share and communicate within the family as well as to share their interactions at school with family members. Copyright © 2016 ACM.}, note = {cited By 4}, keywords = {Autism Spectrum Disorders, Behaviour, Children, Communication, Diseases, Human Computer Interaction, Interactive Computer Systems, iPad Applications, MyCalendar, Photo and Video, Socialisation}, pubstate = {published}, tppubtype = {conference} } This paper presents a study in which a mobile application, 'MyCalendar', was trialled with children on the autism spectrum and their families. In previous work, we described how the MyCalendar app supported communication across both home and school settings through photos and videos of the child's activities, presented in the format of a visual calendar. These visuals supported the child to communicate and socialise and to recall activities and helped adults to better understand the child holistically. This note augments previous work on MyCalendar by focusing on interactions at home within the family. Findings revealed that routine review of activities documented in MyCalendar enabled children to participate more in family conversations, extended their time spent interacting socially, and reinforced social relationships. This gave the children on the autism spectrum greater opportunity to share and communicate within the family as well as to share their interactions at school with family members. Copyright © 2016 ACM. |
2013 |
Selvaraj, J; Murugappan, M; Wan, K; Yaacob, S Classification of emotional states from electrocardiogram signals: A non-linear approach based on hurst Journal Article BioMedical Engineering Online, 12 (1), 2013, ISSN: 1475925X, (cited By 42). Abstract | Links | BibTeX | Tags: Adolescent, Adult, Aged, Article, Audio-Visual Stimulus, Autonomous Nervous Systems, Children, Classification Accuracy, Computer Based Training, Computer-Assisted, Electrocardiogram Signal, Electrocardiography, Emotion, Female, Fuzzy K-nearest Neighbor, Higher-Order Statistic (HOS), Human, Intellectual Disability, Interactive Computer Systems, Methodology, Middle Aged, Nonlinear Dynamics, Nonlinear System, Procedures, Real Time Systems, Signal Processing, Statistics, Young Adult @article{Selvaraj2013, title = {Classification of emotional states from electrocardiogram signals: A non-linear approach based on hurst}, author = {J Selvaraj and M Murugappan and K Wan and S Yaacob}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84879017985&doi=10.1186%2f1475-925X-12-44&partnerID=40&md5=18c5309ac9f3017f455480f1ff732a30}, doi = {10.1186/1475-925X-12-44}, issn = {1475925X}, year = {2013}, date = {2013-01-01}, journal = {BioMedical Engineering Online}, volume = {12}, number = {1}, publisher = {BioMed Central Ltd.}, abstract = {Background: Identifying the emotional state is helpful in applications involving patients with autism and other intellectual disabilities; computer-based training, human computer interaction etc. Electrocardiogram (ECG) signals, being an activity of the autonomous nervous system (ANS), reflect the underlying true emotional state of a person. However, the performance of various methods developed so far lacks accuracy, and more robust methods need to be developed to identify the emotional pattern associated with ECG signals.Methods: Emotional ECG data was obtained from sixty participants by inducing the six basic emotional states (happiness, sadness, fear, disgust, surprise and neutral) using audio-visual stimuli. The non-linear feature 'Hurst' was computed using Rescaled Range Statistics (RRS) and Finite Variance Scaling (FVS) methods. New Hurst features were proposed by combining the existing RRS and FVS methods with Higher Order Statistics (HOS). The features were then classified using four classifiers - Bayesian Classifier, Regression Tree, K- nearest neighbor and Fuzzy K-nearest neighbor. Seventy percent of the features were used for training and thirty percent for testing the algorithm.Results: Analysis of Variance (ANOVA) conveyed that Hurst and the proposed features were statistically significant (p < 0.001). Hurst computed using RRS and FVS methods showed similar classification accuracy. The features obtained by combining FVS and HOS performed better with a maximum accuracy of 92.87% and 76.45% for classifying the six emotional states using random and subject independent validation respectively.Conclusions: The results indicate that the combination of non-linear analysis and HOS tend to capture the finer emotional changes that can be seen in healthy ECG data. This work can be further fine tuned to develop a real time system. © 2013 Selvaraj et al.; licensee BioMed Central Ltd.}, note = {cited By 42}, keywords = {Adolescent, Adult, Aged, Article, Audio-Visual Stimulus, Autonomous Nervous Systems, Children, Classification Accuracy, Computer Based Training, Computer-Assisted, Electrocardiogram Signal, Electrocardiography, Emotion, Female, Fuzzy K-nearest Neighbor, Higher-Order Statistic (HOS), Human, Intellectual Disability, Interactive Computer Systems, Methodology, Middle Aged, Nonlinear Dynamics, Nonlinear System, Procedures, Real Time Systems, Signal Processing, Statistics, Young Adult}, pubstate = {published}, tppubtype = {article} } Background: Identifying the emotional state is helpful in applications involving patients with autism and other intellectual disabilities; computer-based training, human computer interaction etc. Electrocardiogram (ECG) signals, being an activity of the autonomous nervous system (ANS), reflect the underlying true emotional state of a person. However, the performance of various methods developed so far lacks accuracy, and more robust methods need to be developed to identify the emotional pattern associated with ECG signals.Methods: Emotional ECG data was obtained from sixty participants by inducing the six basic emotional states (happiness, sadness, fear, disgust, surprise and neutral) using audio-visual stimuli. The non-linear feature 'Hurst' was computed using Rescaled Range Statistics (RRS) and Finite Variance Scaling (FVS) methods. New Hurst features were proposed by combining the existing RRS and FVS methods with Higher Order Statistics (HOS). The features were then classified using four classifiers - Bayesian Classifier, Regression Tree, K- nearest neighbor and Fuzzy K-nearest neighbor. Seventy percent of the features were used for training and thirty percent for testing the algorithm.Results: Analysis of Variance (ANOVA) conveyed that Hurst and the proposed features were statistically significant (p < 0.001). Hurst computed using RRS and FVS methods showed similar classification accuracy. The features obtained by combining FVS and HOS performed better with a maximum accuracy of 92.87% and 76.45% for classifying the six emotional states using random and subject independent validation respectively.Conclusions: The results indicate that the combination of non-linear analysis and HOS tend to capture the finer emotional changes that can be seen in healthy ECG data. This work can be further fine tuned to develop a real time system. © 2013 Selvaraj et al.; licensee BioMed Central Ltd. |
Testingadminnaacuitm2020-05-28T06:49:14+00:00
2017 |
MyCalendar: Supporting children on the autism spectrum to learn language and appropriate behaviour Conference Association for Computing Machinery, 2017, ISBN: 9781450353793, (cited By 1). |
2016 |
MyCalendar: Supporting families to communicate with their child on the autism spectrum Conference Association for Computing Machinery, Inc, 2016, ISBN: 9781450346184, (cited By 4). |
2013 |
Classification of emotional states from electrocardiogram signals: A non-linear approach based on hurst Journal Article BioMedical Engineering Online, 12 (1), 2013, ISSN: 1475925X, (cited By 42). |