Continuous ambulatory monitoring using wearable physiological sensors and smartphone assessments identified digital phenotypes for daily-life stress detection with an average F1-score of 0.43.
Cross-Sectional (n=1,002)
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Does continuous ambulatory monitoring with wearable devices detect physiological changes associated with self-reported daily-life stress in healthy adults?
Large-scale ambulatory monitoring using wearable devices can identify digital phenotypes and physiological changes associated with daily-life stress, highlighting the potential for personalized stress detection models.
Physiological signals have shown to be reliable indicators of stress in laboratory studies, yet large-scale ambulatory validation is lacking. We present a large-scale cross-sectional study for ambulatory stress detection, consisting of 1002 subjects, containing subjects' demographics, baseline psychological information, and five consecutive days of free-living physiological and contextual measurements, collected through wearable devices and smartphones. This dataset represents a healthy population, showing associations between wearable physiological signals and self-reported daily-life stress. Using a data-driven approach, we identified digital phenotypes characterized by self-reported poor health indicators and high depression, anxiety and stress scores that are associated with blunted physiological responses to stress. These results emphasize the need for large-scale collections of multi-sensor data, to build personalized stress models for precision medicine.
Smets et al. (Thu,) conducted a cross-sectional in Daily-life stress in healthy volunteers (n=1,002). Wearable physiological monitoring (ECG, SC, ST) and smartphone EMAs was evaluated on Classification performance (F1-score) of physiological features to self-reported stress (95% CI 0.05-0.86). Continuous ambulatory monitoring using wearable physiological sensors and smartphone assessments identified digital phenotypes for daily-life stress detection with an average F1-score of 0.43.