Stress Detection of Children With ASD Using Physiological Signals

Sevgi Nur Bilgin Aktas; Pinar Uluer; Buket Coskun; Elif Toprak; Duygun Erol Barkana; Hatice Kose; Tatjana Zorcec; Ben Robins; Agnieszka Landowska

doi:10.1109/siu55565.2022.9864668

Stress Detection of Children With ASD Using Physiological Signals

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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Authors (9)

Sevgi Nur Bilgin Aktas
Pinar Uluer
Buket Coskun
Elif Toprak
Duygun Erol Barkana
Hatice Kose
Tatjana Zorcec
Ben Robins
Agnieszka Landowska dr hab. inż.

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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

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