Multimodal data collection framework for mental stress monitoring

Saewon Kye, Junhyung Moon, Juneil Lee, Inho Choi, Dongmi Cheon, Kyoungwoo Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Accurate recognition of people's responses to stress and timely management of stress is one of the important aspects of maintaining good health. However, recognizing such reactions is difficult since people react to stressful events in various ways. Accordingly, we propose a multi-modal stress monitoring framework to examine people's physiological and behavioral reactions to stressors. Our framework consists of (i) multimodal data collection related to mental stress, (ii) stress inducing experiment in a laboratory, and (iii) signal examination software in real-time and after the data collection. Through preliminary experiments, we have examined how people show various reactions to different kinds of stressful tasks. Finally, based on the proposed framework, we will establish a database contributing to the mental health sensing research.

Original languageEnglish
Title of host publicationUbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers
PublisherAssociation for Computing Machinery, Inc
Pages822-829
Number of pages8
ISBN (Electronic)9781450351904
DOIs
Publication statusPublished - 2017 Sep 11
Event2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017 - Maui, United States
Duration: 2017 Sep 112017 Sep 15

Other

Other2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017
CountryUnited States
CityMaui
Period17/9/1117/9/15

Fingerprint

Monitoring
Health
Experiments

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

Cite this

Kye, S., Moon, J., Lee, J., Choi, I., Cheon, D., & Lee, K. (2017). Multimodal data collection framework for mental stress monitoring. In UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers (pp. 822-829). Association for Computing Machinery, Inc. https://doi.org/10.1145/3123024.3125616
Kye, Saewon ; Moon, Junhyung ; Lee, Juneil ; Choi, Inho ; Cheon, Dongmi ; Lee, Kyoungwoo. / Multimodal data collection framework for mental stress monitoring. UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc, 2017. pp. 822-829
@inproceedings{3ad6c8f51928423baf0d31aa195c0904,
title = "Multimodal data collection framework for mental stress monitoring",
abstract = "Accurate recognition of people's responses to stress and timely management of stress is one of the important aspects of maintaining good health. However, recognizing such reactions is difficult since people react to stressful events in various ways. Accordingly, we propose a multi-modal stress monitoring framework to examine people's physiological and behavioral reactions to stressors. Our framework consists of (i) multimodal data collection related to mental stress, (ii) stress inducing experiment in a laboratory, and (iii) signal examination software in real-time and after the data collection. Through preliminary experiments, we have examined how people show various reactions to different kinds of stressful tasks. Finally, based on the proposed framework, we will establish a database contributing to the mental health sensing research.",
author = "Saewon Kye and Junhyung Moon and Juneil Lee and Inho Choi and Dongmi Cheon and Kyoungwoo Lee",
year = "2017",
month = "9",
day = "11",
doi = "10.1145/3123024.3125616",
language = "English",
pages = "822--829",
booktitle = "UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers",
publisher = "Association for Computing Machinery, Inc",

}

Kye, S, Moon, J, Lee, J, Choi, I, Cheon, D & Lee, K 2017, Multimodal data collection framework for mental stress monitoring. in UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc, pp. 822-829, 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017, Maui, United States, 17/9/11. https://doi.org/10.1145/3123024.3125616

Multimodal data collection framework for mental stress monitoring. / Kye, Saewon; Moon, Junhyung; Lee, Juneil; Choi, Inho; Cheon, Dongmi; Lee, Kyoungwoo.

UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc, 2017. p. 822-829.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Multimodal data collection framework for mental stress monitoring

AU - Kye, Saewon

AU - Moon, Junhyung

AU - Lee, Juneil

AU - Choi, Inho

AU - Cheon, Dongmi

AU - Lee, Kyoungwoo

PY - 2017/9/11

Y1 - 2017/9/11

N2 - Accurate recognition of people's responses to stress and timely management of stress is one of the important aspects of maintaining good health. However, recognizing such reactions is difficult since people react to stressful events in various ways. Accordingly, we propose a multi-modal stress monitoring framework to examine people's physiological and behavioral reactions to stressors. Our framework consists of (i) multimodal data collection related to mental stress, (ii) stress inducing experiment in a laboratory, and (iii) signal examination software in real-time and after the data collection. Through preliminary experiments, we have examined how people show various reactions to different kinds of stressful tasks. Finally, based on the proposed framework, we will establish a database contributing to the mental health sensing research.

AB - Accurate recognition of people's responses to stress and timely management of stress is one of the important aspects of maintaining good health. However, recognizing such reactions is difficult since people react to stressful events in various ways. Accordingly, we propose a multi-modal stress monitoring framework to examine people's physiological and behavioral reactions to stressors. Our framework consists of (i) multimodal data collection related to mental stress, (ii) stress inducing experiment in a laboratory, and (iii) signal examination software in real-time and after the data collection. Through preliminary experiments, we have examined how people show various reactions to different kinds of stressful tasks. Finally, based on the proposed framework, we will establish a database contributing to the mental health sensing research.

UR - http://www.scopus.com/inward/record.url?scp=85030863126&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85030863126&partnerID=8YFLogxK

U2 - 10.1145/3123024.3125616

DO - 10.1145/3123024.3125616

M3 - Conference contribution

SP - 822

EP - 829

BT - UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers

PB - Association for Computing Machinery, Inc

ER -

Kye S, Moon J, Lee J, Choi I, Cheon D, Lee K. Multimodal data collection framework for mental stress monitoring. In UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc. 2017. p. 822-829 https://doi.org/10.1145/3123024.3125616