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 inter- vention. 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.
Authors
- Sevgi Nur Bilgin Aktas,
- Pinar Uluer,
- Buket Coskun,
- Elif Toprak,
- Duygun Erol Barkana,
- Hatice Kose,
- Tatjana Zorcec,
- Ben Robins,
- dr hab. inż. Agnieszka Landowska link open in new tab
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1109/siu55565.2022.9864668
- Category
- Aktywność konferencyjna
- Type
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Language
- angielski
- Publication year
- 2022
