Towards artificial intelligence driven stress monitoring for mental wellbeing tracking during COVID-19

Sabrina Jesmin; M. Shamim Kaiser; Mufti Mahmud

doi:10.1109/WIIAT50758.2020.00130

Towards artificial intelligence driven stress monitoring for mental wellbeing tracking during COVID-19

Sabrina Jesmin
, M. Shamim Kaiser
, Mufti Mahmud

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

31 Scopus citations

Abstract

The stresses and patterns of life are often demanding and require physical and psychological actions to support themselves. An individual responds to mental stresses that is potentially detrimental to health. The mental stress may result hormonal imbalance and noxious stimulus in the body. The 2 (SARS-COV-2) or COVID-19 infection not only stopped people's daily routine, but also created many political, social, financial, psychological and health problems. Mental stress has become common during this pandemic with limited opportunity to reach outhealth professionals in person. We have proposed artificial intelligence driven cloud based self-stress detection model which takes physiological signals such as Galvanic Skin Response, Heart Rate Variability, Peripheral Capillary Oxygen Saturation to determine the stress level. The sensors are embedded into a wearable device and collects physiological signals and thereby detect stress level of an individual. Finally, we have also suggested some recommendations to manage stress for any individual during COVID-19 for their wellbeing.

Original language	English
Title of host publication	Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020
Editors	Jing He, Hemant Purohit, Guangyan Huang, Xiaoying Gao, Ke Deng
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	845-851
Number of pages	7
ISBN (Electronic)	9781665419246
DOIs	https://doi.org/10.1109/WIIAT50758.2020.00130
State	Published - Dec 2020
Externally published	Yes
Event	2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020 - Virtual, Online Duration: 14 Dec 2020 → 17 Dec 2020

Publication series

Name	Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020

Conference

Conference	2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020
City	Virtual, Online
Period	14/12/20 → 17/12/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

Artificial Intelligence
COVID19
Neuro Science
Stress monitoring

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Software

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/WIIAT50758.2020.00130

Cite this

Jesmin, S., Kaiser, M. S., & Mahmud, M. (2020). Towards artificial intelligence driven stress monitoring for mental wellbeing tracking during COVID-19. In J. He, H. Purohit, G. Huang, X. Gao, & K. Deng (Eds.), Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020 (pp. 845-851). Article 9457769 (Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WIIAT50758.2020.00130

Jesmin, Sabrina ; Kaiser, M. Shamim ; Mahmud, Mufti. / Towards artificial intelligence driven stress monitoring for mental wellbeing tracking during COVID-19. Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020. editor / Jing He ; Hemant Purohit ; Guangyan Huang ; Xiaoying Gao ; Ke Deng. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 845-851 (Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020).

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title = "Towards artificial intelligence driven stress monitoring for mental wellbeing tracking during COVID-19",

abstract = "The stresses and patterns of life are often demanding and require physical and psychological actions to support themselves. An individual responds to mental stresses that is potentially detrimental to health. The mental stress may result hormonal imbalance and noxious stimulus in the body. The 2 (SARS-COV-2) or COVID-19 infection not only stopped people's daily routine, but also created many political, social, financial, psychological and health problems. Mental stress has become common during this pandemic with limited opportunity to reach outhealth professionals in person. We have proposed artificial intelligence driven cloud based self-stress detection model which takes physiological signals such as Galvanic Skin Response, Heart Rate Variability, Peripheral Capillary Oxygen Saturation to determine the stress level. The sensors are embedded into a wearable device and collects physiological signals and thereby detect stress level of an individual. Finally, we have also suggested some recommendations to manage stress for any individual during COVID-19 for their wellbeing.",

keywords = "Artificial Intelligence, COVID19, Neuro Science, Stress monitoring",

author = "Sabrina Jesmin and Kaiser, \{M. Shamim\} and Mufti Mahmud",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020 ; Conference date: 14-12-2020 Through 17-12-2020",

year = "2020",

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doi = "10.1109/WIIAT50758.2020.00130",

language = "English",

series = "Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020",

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Jesmin, S, Kaiser, MS & Mahmud, M 2020, Towards artificial intelligence driven stress monitoring for mental wellbeing tracking during COVID-19. in J He, H Purohit, G Huang, X Gao & K Deng (eds), Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020., 9457769, Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020, Institute of Electrical and Electronics Engineers Inc., pp. 845-851, 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020, Virtual, Online, 14/12/20. https://doi.org/10.1109/WIIAT50758.2020.00130

Towards artificial intelligence driven stress monitoring for mental wellbeing tracking during COVID-19. / Jesmin, Sabrina; Kaiser, M. Shamim; Mahmud, Mufti.
Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020. ed. / Jing He; Hemant Purohit; Guangyan Huang; Xiaoying Gao; Ke Deng. Institute of Electrical and Electronics Engineers Inc., 2020. p. 845-851 9457769 (Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Towards artificial intelligence driven stress monitoring for mental wellbeing tracking during COVID-19

AU - Jesmin, Sabrina

AU - Kaiser, M. Shamim

AU - Mahmud, Mufti

PY - 2020/12

Y1 - 2020/12

N2 - The stresses and patterns of life are often demanding and require physical and psychological actions to support themselves. An individual responds to mental stresses that is potentially detrimental to health. The mental stress may result hormonal imbalance and noxious stimulus in the body. The 2 (SARS-COV-2) or COVID-19 infection not only stopped people's daily routine, but also created many political, social, financial, psychological and health problems. Mental stress has become common during this pandemic with limited opportunity to reach outhealth professionals in person. We have proposed artificial intelligence driven cloud based self-stress detection model which takes physiological signals such as Galvanic Skin Response, Heart Rate Variability, Peripheral Capillary Oxygen Saturation to determine the stress level. The sensors are embedded into a wearable device and collects physiological signals and thereby detect stress level of an individual. Finally, we have also suggested some recommendations to manage stress for any individual during COVID-19 for their wellbeing.

AB - The stresses and patterns of life are often demanding and require physical and psychological actions to support themselves. An individual responds to mental stresses that is potentially detrimental to health. The mental stress may result hormonal imbalance and noxious stimulus in the body. The 2 (SARS-COV-2) or COVID-19 infection not only stopped people's daily routine, but also created many political, social, financial, psychological and health problems. Mental stress has become common during this pandemic with limited opportunity to reach outhealth professionals in person. We have proposed artificial intelligence driven cloud based self-stress detection model which takes physiological signals such as Galvanic Skin Response, Heart Rate Variability, Peripheral Capillary Oxygen Saturation to determine the stress level. The sensors are embedded into a wearable device and collects physiological signals and thereby detect stress level of an individual. Finally, we have also suggested some recommendations to manage stress for any individual during COVID-19 for their wellbeing.

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SP - 845

EP - 851

BT - Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020

A2 - He, Jing

A2 - Purohit, Hemant

A2 - Huang, Guangyan

A2 - Gao, Xiaoying

A2 - Deng, Ke

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 14 December 2020 through 17 December 2020

ER -

Jesmin S, Kaiser MS, Mahmud M. Towards artificial intelligence driven stress monitoring for mental wellbeing tracking during COVID-19. In He J, Purohit H, Huang G, Gao X, Deng K, editors, Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 845-851. 9457769. (Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020). doi: 10.1109/WIIAT50758.2020.00130

Towards artificial intelligence driven stress monitoring for mental wellbeing tracking during COVID-19

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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Cite this