Wearable Device Uses Sleep Data to Identify Stress Risk

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Wearable Device Uses Sleep Data to Identify Stress Risk
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A wearable device can provide clues to stress levels reflected in sleep data, paving the way for identifying biomarkers that flag individuals needing additional support.

Decreased total sleep time and increased resting heart rate , heart rate variability , and average nightly respiratory rate as measured by a multisensor device worn during sleep accurately correlated with self-reported stress levels in college students, a new study suggests. Investigators say the findings support the potential utility of wearable devices to collect data that identify young adult s at greatest risk for stress.

The researchers used mixed-effects regression models to identify associations between perceived stress scores and average nightly TST, RHR, HRV, and ARR.Consistent associations were found between perceived stress scores and TST, RHR, HRV, and ARR, which persisted even after controlling for gender and week of the semester.

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