RT Journal Article
SR Electronic
T1 Using wearable biosensors and ecological momentary assessments for the detection of prolonged stress in real life
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.06.29.450360
DO 10.1101/2021.06.29.450360
A1 Tutunji, Rayyan
A1 Kogias, Nikos
A1 Kapteijns, Bob
A1 Krentz, Martin
A1 Krause, Florian
A1 Vassena, Eliana
A1 Hermans, Erno
YR 2021
UL http://biorxiv.org/content/early/2021/07/14/2021.06.29.450360.abstract
AB Emerging efforts toward prevention of stress-related mental disorders have created a need for unobtrusive real-life monitoring of stress-related symptoms. We used ecological momentary assessments (EMA) combined with wearable biosensors to investigate whether these can be used to detect periods of prolonged stress. During stressful high-stake exam (versus control) weeks, participants reported increased negative affect and decreased positive affect. Intriguingly, physiological arousal was decreased on average during the exam week. Time-resolved analyses revealed peaks in physiological arousal associated with both self-reported stress and self-reported positive affect, while the overall decrease in physiological arousal was mediated by lower positive affect during the stress period. We then used machine learning to show that a combination of EMA and physiology yields optimal classification of week types. Our findings highlight the potential of wearable biosensors in stress-related mental-health monitoring, but critically show that psychological context is essential for interpreting physiological arousal detected using these devices.Teaser Smartwatches combined with daily diaries of mood can detect stress periods using individualized machine learning models.Competing Interest StatementThe authors have declared no competing interest.