The University of Michigan (U-M)'s Daniel Forger and colleagues crafted an algorithm that extracts an individual’s circadian rhythm from heart rate data collected by their smartwatch.
The program rejects data collected during sleep, concentrating on data gleaned while the person is awake, then accounts for whether their heart rate is affected by their activity, or by the stress hormone cortisol as a result of exercise, posture, or meals.
Forger said, "We've shown that you can take a wearable signal and directly measure circadian rhythms in the real world, and the real world has so many things that affect circadian rhythms that you aren't going to measure in the lab."
From University of Michigan News
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