Stress Detection of Children with Autism using Physiological Signals in Kaspar Robot-Based Intervention Studies

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

doi:10.1109/BioRob52689.2022.9925485

Stress Detection of Children with Autism using Physiological Signals in Kaspar Robot-Based Intervention Studies

Buket Coskun, Pinar Uluer, Elif Toprak, Duygun Erol Barkana, Hatice Kose, Tatjana Zorcec, Ben Robins, Agnieszka Landowska

Yapay Zeka ve Veri Mühendisliği Bölümü

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

7 Atıf (Scopus)

Özet

This study aims to develop a stress detection system using the blood volume pulse (BVP) signals of children with Autism Spectrum Disorder (ASD) during robot-based intervention. This study presents the heart rate variability (HRV) analysis method to detect the stress, where HRV features are extracted from raw BVP signals recorded from an E4 wristband during interaction studies with the social robot Kaspar. Low frequency power (LF) and high frequency power (HF) features are analyzed, and the results are verified with facial emotion analysis of the children with ASD. 21 children from 3 countries participated in the study. The results showed that physiological signals combined with affective state labels may predict the stress of children, and the children were not stressed overall their interaction with the Kaspar robot. In specific cases, the children started their session as stressed but their stress declined by the end of the session. These findings are also supported by the results of the vision-based affective state analysis.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	BioRob 2022 - 9th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics
Yayınlayan	IEEE Computer Society
ISBN (Elektronik)	9781665458498
DOI'lar	https://doi.org/10.1109/BioRob52689.2022.9925485
Yayın durumu	Yayınlandı - 2022
Etkinlik	9th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2022 - Seoul, Korea, Republic of Süre: 21 Ağu 2022 → 24 Ağu 2022

Yayın serisi

Adı	Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics
Hacim	2022-August
ISSN (Basılı)	2155-1774

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	9th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2022
Ülke/Bölge	Korea, Republic of
Şehir	Seoul
Periyot	21/08/22 → 24/08/22

Bibliyografik not

Publisher Copyright:
© 2022 IEEE.

Belgeye Erişim

10.1109/BioRob52689.2022.9925485

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Coskun, B., Uluer, P., Toprak, E., Barkana, D. E., Kose, H., Zorcec, T., Robins, B., & Landowska, A. (2022). Stress Detection of Children with Autism using Physiological Signals in Kaspar Robot-Based Intervention Studies. In BioRob 2022 - 9th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics; Hac. 2022-August). IEEE Computer Society. https://doi.org/10.1109/BioRob52689.2022.9925485

Coskun, Buket ; Uluer, Pinar ; Toprak, Elif et al. / Stress Detection of Children with Autism using Physiological Signals in Kaspar Robot-Based Intervention Studies. BioRob 2022 - 9th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics. IEEE Computer Society, 2022. (Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics).

@inproceedings{092a60ecf45a4a648edcaf222d5a3a63,

title = "Stress Detection of Children with Autism using Physiological Signals in Kaspar Robot-Based Intervention Studies",

abstract = "This study aims to develop a stress detection system using the blood volume pulse (BVP) signals of children with Autism Spectrum Disorder (ASD) during robot-based intervention. This study presents the heart rate variability (HRV) analysis method to detect the stress, where HRV features are extracted from raw BVP signals recorded from an E4 wristband during interaction studies with the social robot Kaspar. Low frequency power (LF) and high frequency power (HF) features are analyzed, and the results are verified with facial emotion analysis of the children with ASD. 21 children from 3 countries participated in the study. The results showed that physiological signals combined with affective state labels may predict the stress of children, and the children were not stressed overall their interaction with the Kaspar robot. In specific cases, the children started their session as stressed but their stress declined by the end of the session. These findings are also supported by the results of the vision-based affective state analysis.",

keywords = "affective state, physiological signals, Robot-based intervention, stress detection",

author = "Buket Coskun and Pinar Uluer and Elif Toprak and Barkana, {Duygun Erol} and Hatice Kose and Tatjana Zorcec and Ben Robins and Agnieszka Landowska",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 9th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2022 ; Conference date: 21-08-2022 Through 24-08-2022",

year = "2022",

doi = "10.1109/BioRob52689.2022.9925485",

language = "English",

series = "Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics",

publisher = "IEEE Computer Society",

booktitle = "BioRob 2022 - 9th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics",

address = "United States",

}

Coskun, B, Uluer, P, Toprak, E, Barkana, DE, Kose, H, Zorcec, T, Robins, B & Landowska, A 2022, Stress Detection of Children with Autism using Physiological Signals in Kaspar Robot-Based Intervention Studies. in BioRob 2022 - 9th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics. Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, hac. 2022-August, IEEE Computer Society, 9th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2022, Seoul, Korea, Republic of, 21/08/22. https://doi.org/10.1109/BioRob52689.2022.9925485

Stress Detection of Children with Autism using Physiological Signals in Kaspar Robot-Based Intervention Studies. / Coskun, Buket; Uluer, Pinar; Toprak, Elif et al.
BioRob 2022 - 9th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics. IEEE Computer Society, 2022. (Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics; Hac. 2022-August).

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

TY - GEN

T1 - Stress Detection of Children with Autism using Physiological Signals in Kaspar Robot-Based Intervention Studies

AU - Coskun, Buket

AU - Uluer, Pinar

AU - Toprak, Elif

AU - Barkana, Duygun Erol

AU - Kose, Hatice

AU - Zorcec, Tatjana

AU - Robins, Ben

AU - Landowska, Agnieszka

PY - 2022

Y1 - 2022

N2 - This study aims to develop a stress detection system using the blood volume pulse (BVP) signals of children with Autism Spectrum Disorder (ASD) during robot-based intervention. This study presents the heart rate variability (HRV) analysis method to detect the stress, where HRV features are extracted from raw BVP signals recorded from an E4 wristband during interaction studies with the social robot Kaspar. Low frequency power (LF) and high frequency power (HF) features are analyzed, and the results are verified with facial emotion analysis of the children with ASD. 21 children from 3 countries participated in the study. The results showed that physiological signals combined with affective state labels may predict the stress of children, and the children were not stressed overall their interaction with the Kaspar robot. In specific cases, the children started their session as stressed but their stress declined by the end of the session. These findings are also supported by the results of the vision-based affective state analysis.

AB - This study aims to develop a stress detection system using the blood volume pulse (BVP) signals of children with Autism Spectrum Disorder (ASD) during robot-based intervention. This study presents the heart rate variability (HRV) analysis method to detect the stress, where HRV features are extracted from raw BVP signals recorded from an E4 wristband during interaction studies with the social robot Kaspar. Low frequency power (LF) and high frequency power (HF) features are analyzed, and the results are verified with facial emotion analysis of the children with ASD. 21 children from 3 countries participated in the study. The results showed that physiological signals combined with affective state labels may predict the stress of children, and the children were not stressed overall their interaction with the Kaspar robot. In specific cases, the children started their session as stressed but their stress declined by the end of the session. These findings are also supported by the results of the vision-based affective state analysis.

KW - affective state

KW - physiological signals

KW - Robot-based intervention

KW - stress detection

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U2 - 10.1109/BioRob52689.2022.9925485

DO - 10.1109/BioRob52689.2022.9925485

M3 - Conference contribution

AN - SCOPUS:85141871986

T3 - Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics

BT - BioRob 2022 - 9th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics

PB - IEEE Computer Society

T2 - 9th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2022

Y2 - 21 August 2022 through 24 August 2022

ER -

Coskun B, Uluer P, Toprak E, Barkana DE, Kose H, Zorcec T et al. Stress Detection of Children with Autism using Physiological Signals in Kaspar Robot-Based Intervention Studies. In BioRob 2022 - 9th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics. IEEE Computer Society. 2022. (Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics). doi: 10.1109/BioRob52689.2022.9925485

Stress Detection of Children with Autism using Physiological Signals in Kaspar Robot-Based Intervention Studies

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