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 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.
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Details
- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Title of issue:
- 2022 30th Signal Processing and Communications Applications Conference (SIU) strony 1 - 4
- Language:
- English
- Publication year:
- 2022
- Bibliographic description:
- Aktas S. N. B., Uluer P., Coskun B., Toprak E., Barkana D. E., Kose H., Zorcec T., Robins B., Landowska A.: Stress Detection of Children With ASD Using Physiological Signals// 2022 30th Signal Processing and Communications Applications Conference (SIU)/ : , 2022, s.1-4
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/siu55565.2022.9864668
- Sources of funding:
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- Free publication
- Verified by:
- Gdańsk University of Technology
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