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المؤلفAlban, Ahmad Qadeib
المؤلفAlhaddad, Ahmad Yaser
المؤلفAl-Ali, Abdulaziz
المؤلفSo, Wing Chee
المؤلفConnor, Olcay
المؤلفAyesh, Malek
المؤلفAhmed Qidwai, Uvais
المؤلفCabibihan, John John
تاريخ الإتاحة2023-11-21T10:37:24Z
تاريخ النشر2023-04-01
اسم المنشورRobotics
المعرّفhttp://dx.doi.org/10.3390/robotics12020055
الاقتباسAlban, A. Q., Alhaddad, A. Y., Al-Ali, A., So, W. C., Connor, O., Ayesh, M., ... & Cabibihan, J. J. (2023). Heart Rate as a Predictor of Challenging Behaviours among Children with Autism from Wearable Sensors in Social Robot Interactions. Robotics, 12(2), 55.‏
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85153765430&origin=inward
معرّف المصادر الموحدhttp://hdl.handle.net/10576/49566
الملخصChildren with autism face challenges in various skills (e.g., communication and social) and they exhibit challenging behaviours. These challenging behaviours represent a challenge to their families, therapists, and caregivers, especially during therapy sessions. In this study, we have investigated several machine learning techniques and data modalities acquired using wearable sensors from children with autism during their interactions with social robots and toys in their potential to detect challenging behaviours. Each child wore a wearable device that collected data. Video annotations of the sessions were used to identify the occurrence of challenging behaviours. Extracted time features (i.e., mean, standard deviation, min, and max) in conjunction with four machine learning techniques were considered to detect challenging behaviors. The heart rate variability (HRV) changes have also been investigated in this study. The XGBoost algorithm has achieved the best performance (i.e., an accuracy of 99%). Additionally, physiological features outperformed the kinetic ones, with the heart rate being the main contributing feature in the prediction performance. One HRV parameter (i.e., RMSSD) was found to correlate with the occurrence of challenging behaviours. This work highlights the importance of developing the tools and methods to detect challenging behaviors among children with autism during aided sessions with social robots.
اللغةen
الناشرMDPI
الموضوعautism
challenging behaviours
machine learning
social robots
wearables
العنوانHeart Rate as a Predictor of Challenging Behaviours among Children with Autism from Wearable Sensors in Social Robot Interactions
النوعArticle
رقم العدد2
رقم المجلد12
dc.accessType Open Access


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