WildStress: exploring rich situational contexts for stress detection in the wild

Short-term experience of stress arousal can be useful in coping with everyday life tasks. However, undergoing intense stressful scenarios frequently and consistently can be damaging for mental and physical health. To detect such stressful scenarios physiological stress models were developed in lab c...

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Bibliographic Details
Main Authors: Toshnazarov, Kobiljon, Lee, Tae Hong, Noh, Youngtae
Format: Conference Proceeding
Language:English
Subjects:
Big Data
context
Human factors
mHealth
Physiology
smartphone
smartwatch
stress
Task analysis
ubiquitous computing
Online Access:Request full text
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Summary:Short-term experience of stress arousal can be useful in coping with everyday life tasks. However, undergoing intense stressful scenarios frequently and consistently can be damaging for mental and physical health. To detect such stressful scenarios physiological stress models were developed in lab conditions, but still showed poor results in daily life settings. Hence, leveraging rich contextual information about user's daily life can help identify stress in uncontrolled daily life environments. To that end, this work details on our research direction, that is to use rich contextual data captured from users' daily lives alongside physiological readings to timely detect in the wild stress.
ISSN:2375-9356
DOI:10.1109/BigComp57234.2023.00091