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AuthorAlban, Ahmad Qadeib
AuthorAyesh, Malek
AuthorAlhaddad, Ahmad Yaser
AuthorKhalid Al-Ali, Abdulaziz
AuthorSo, Wing Chee
AuthorConnor, Olcay
AuthorCabibihan, John John
Available date2023-11-22T07:43:01Z
Publication Date2021-08-08
Publication Name2021 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021
Identifierhttp://dx.doi.org/10.1109/RO-MAN50785.2021.9515459
CitationAlban, A. Q., Ayesh, M., Alhaddad, A. Y., Al-Ali, A. K., So, W. C., Connor, O., & Cabibihan, J. J. (2021, August). Detection of challenging behaviours of children with autism using wearable sensors during interactions with social robots. In 2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN) (pp. 852-857). IEEE.‏
ISBN9781665404921
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85115116950&origin=inward
URIhttp://hdl.handle.net/10576/49598
AbstractAutism spectrum disorder is a neurodevelopmental disorder that is characterized by patterns of behaviours and difficulties with social communication and interaction. Children on the spectrum exhibit atypical, restricted, repetitive, and challenging behaviours. In this study, we investigate the feasibility of integrating wearable sensors and machine learning techniques to detect the occurrence of challenging behaviours in real-time. A session of a child with autism interacting with different stimuli groups that included social robots was annotated with observed challenging behaviors. The child wore a wearable device that captured different motion and physiological signals. Different features and machine learning configurations were investigated to identify the most effective combination. Our results showed that physiological signals in addition to typical kinetic measures led to more accurate predictions. The best features and learning model combination achieved an accuracy of 97%. The findings of this work motivate research toward methods of early detection of challenging behaviours, which may enable the timely intervention by caregivers and possibly by social robots.
Languageen
PublisherIEEE Explore
Subjectsensors
TitleDetection of challenging behaviours of children with autism using wearable sensors during interactions with social robots
TypeConference Paper
Pagination852-857
dc.accessType Abstract Only


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