Predicting Perceived Stress Through Mirco-EMAs and a Flexible Wearable ECG Device

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.