The effects of stress may be alleviated when its impact or a decreased stress-resilience are detected early. This study explores whether wearable-measured sleep and resting HRV in police officers can be predicted by stress-related Ecological Momentary Assessment (EMA) measures in preceding days and predict stress-related EMA outcomes in subsequent days. Eight police officers used an Oura ring to collect daily Total Sleep Time (TST) and resting Heart Rate Variability (HRV) and an EMA app for measuring demands, stress, mental exhaustion, and vigor during 15–55 weeks. Vector Autoregression (VAR) models were created and complemented by Granger causation tests and Impulse Response Function visualizations. Demands negatively predicted TST and HRV in one participant. TST negatively predicted demands, stress, and mental exhaustion in two, three, and five participants, respectively, and positively predicted vigor in five participants. HRV negatively predicted demands in two participants, and stress and mental exhaustion in one participant. Changes in HRV lasted longer than those in TST. Bidirectional associations of TST and resting HRV with stress-related outcomes were observed at a weak-to-moderate strength, but not consistently across participants. TST and resting HRV are more consistent predictors of stress-resilience in upcoming days than indicators of stress-related measures in prior days.
Translated title of the contributionHet voorspellen van subjectieve gevoelens van stress met behulp van door draagbare technologie gemeten slaap en hartritme-variabiliteit
Original languageEnglish
Number of pages1
Publication statusPublished - 20 Apr 2023
EventNWO ICT.OPEN 2023 - Jaarbeurs, Utrecht, Netherlands
Duration: 19 Apr 202320 Apr 2023


ConferenceNWO ICT.OPEN 2023
Internet address


  • HRV
  • heart rate variability
  • wearable technology
  • sleep


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