Stress Detection of Children With ASD Using Physiological Signals
Date Issued
2022-08-29
Author(s)
Sevgi Nur Bilgin Aktaş
Pınar Uluer
Buket Coşkun
Elif Toprak
Duygun Erol Barkana
Hatice Köse
Ben Robins
Agnieszka Landowska
DOI
10.1109/SIU55565.2022.9864668
Abstract
This paper proposes a physiological signal-based stress detection approach for children with autism spectrum disorder (ASD) to be used in social and assistive robot intervention. Electrodermal activity (EDA) and blood volume pulse (BVP) signals are collected with an E4 smart wristband from children with ASD in different countries. The peak count and signal amplitude features are derived from EDA signal and used in order to detect the stress of children based on the previously provided reference baselines. Furthermore, a comparison has been made with the stress values determined using low frequency (LF) and high frequency (HF) values extracted from BVP signal.