Poster:Predicting perceived stress through mirco-EMAs and a flexible wearable ECG device

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

Abstract

Self-reported perceived stress does not often correlate with physiologic and behavioral stress response. Current perceived stress self-report assessment methods require users to answer many questions at different time points of the day. Reducing it to one question at multiple time points throughout the day, using microinteraction-based Ecological Momentary Assessment (micro-EMA) allows us to identify smaller or more subtle changes in physiology and corresponding emotional reactions that reflect experiences of stress. We identify the optimal micro-EMAs by finding single item questions that correlate with intended stressors, and are most predictive from physiological signals. Physiological signals were collected in lab with a flexible wearable sensor that captured R-R IBI and motion from 22 female participants performing multiple stressful and non-stressful activities. Results show that simply asking how stressed a person is with a 7-scale Likert scale response results in 0.63 correlation with intended stressful activities, and a 68% F1-Score in predicting stress. We further report on acceptability and feasibility of using this sensor.

Original languageEnglish (US)
Title of host publicationUbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers
PublisherAssociation for Computing Machinery, Inc
Pages106-109
Number of pages4
ISBN (Electronic)9781450359665
DOIs
StatePublished - Oct 8 2018
Event2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018 - Singapore, Singapore
Duration: Oct 8 2018Oct 12 2018

Publication series

NameUbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers

Other

Other2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018
CountrySingapore
CitySingapore
Period10/8/1810/12/18

Fingerprint

Electrocardiography
Physiology
Sensors
Wearable sensors

Keywords

  • EMA
  • Flexible Wearable Sensor
  • Machine Learning
  • Micro-EMA
  • Stress

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Information Systems

Cite this

King, Z., Wakschlag, L. S., Moskowitz, J. T., & Alshurafa, N. (2018). Poster:Predicting perceived stress through mirco-EMAs and a flexible wearable ECG device. In UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers (pp. 106-109). (UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers). Association for Computing Machinery, Inc. https://doi.org/10.1145/3267305.3267639
King, Zachary ; Wakschlag, Lauren S ; Moskowitz, Judith Tedlie ; Alshurafa, Nabil. / Poster:Predicting perceived stress through mirco-EMAs and a flexible wearable ECG device. UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc, 2018. pp. 106-109 (UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers).
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title = "Poster:Predicting perceived stress through mirco-EMAs and a flexible wearable ECG device",
abstract = "Self-reported perceived stress does not often correlate with physiologic and behavioral stress response. Current perceived stress self-report assessment methods require users to answer many questions at different time points of the day. Reducing it to one question at multiple time points throughout the day, using microinteraction-based Ecological Momentary Assessment (micro-EMA) allows us to identify smaller or more subtle changes in physiology and corresponding emotional reactions that reflect experiences of stress. We identify the optimal micro-EMAs by finding single item questions that correlate with intended stressors, and are most predictive from physiological signals. Physiological signals were collected in lab with a flexible wearable sensor that captured R-R IBI and motion from 22 female participants performing multiple stressful and non-stressful activities. Results show that simply asking how stressed a person is with a 7-scale Likert scale response results in 0.63 correlation with intended stressful activities, and a 68{\%} F1-Score in predicting stress. We further report on acceptability and feasibility of using this sensor.",
keywords = "EMA, Flexible Wearable Sensor, Machine Learning, Micro-EMA, Stress",
author = "Zachary King and Wakschlag, {Lauren S} and Moskowitz, {Judith Tedlie} and Nabil Alshurafa",
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King, Z, Wakschlag, LS, Moskowitz, JT & Alshurafa, N 2018, Poster:Predicting perceived stress through mirco-EMAs and a flexible wearable ECG device. in UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers. UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers, Association for Computing Machinery, Inc, pp. 106-109, 2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018, Singapore, Singapore, 10/8/18. https://doi.org/10.1145/3267305.3267639

Poster:Predicting perceived stress through mirco-EMAs and a flexible wearable ECG device. / King, Zachary; Wakschlag, Lauren S; Moskowitz, Judith Tedlie; Alshurafa, Nabil.

UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc, 2018. p. 106-109 (UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers).

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

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T1 - Poster:Predicting perceived stress through mirco-EMAs and a flexible wearable ECG device

AU - King, Zachary

AU - Wakschlag, Lauren S

AU - Moskowitz, Judith Tedlie

AU - Alshurafa, Nabil

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N2 - Self-reported perceived stress does not often correlate with physiologic and behavioral stress response. Current perceived stress self-report assessment methods require users to answer many questions at different time points of the day. Reducing it to one question at multiple time points throughout the day, using microinteraction-based Ecological Momentary Assessment (micro-EMA) allows us to identify smaller or more subtle changes in physiology and corresponding emotional reactions that reflect experiences of stress. We identify the optimal micro-EMAs by finding single item questions that correlate with intended stressors, and are most predictive from physiological signals. Physiological signals were collected in lab with a flexible wearable sensor that captured R-R IBI and motion from 22 female participants performing multiple stressful and non-stressful activities. Results show that simply asking how stressed a person is with a 7-scale Likert scale response results in 0.63 correlation with intended stressful activities, and a 68% F1-Score in predicting stress. We further report on acceptability and feasibility of using this sensor.

AB - Self-reported perceived stress does not often correlate with physiologic and behavioral stress response. Current perceived stress self-report assessment methods require users to answer many questions at different time points of the day. Reducing it to one question at multiple time points throughout the day, using microinteraction-based Ecological Momentary Assessment (micro-EMA) allows us to identify smaller or more subtle changes in physiology and corresponding emotional reactions that reflect experiences of stress. We identify the optimal micro-EMAs by finding single item questions that correlate with intended stressors, and are most predictive from physiological signals. Physiological signals were collected in lab with a flexible wearable sensor that captured R-R IBI and motion from 22 female participants performing multiple stressful and non-stressful activities. Results show that simply asking how stressed a person is with a 7-scale Likert scale response results in 0.63 correlation with intended stressful activities, and a 68% F1-Score in predicting stress. We further report on acceptability and feasibility of using this sensor.

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M3 - Conference contribution

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King Z, Wakschlag LS, Moskowitz JT, Alshurafa N. Poster:Predicting perceived stress through mirco-EMAs and a flexible wearable ECG device. In UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc. 2018. p. 106-109. (UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers). https://doi.org/10.1145/3267305.3267639