Machine learning models estimate circadian phase from about 8 hours of light and activity wearable data with 1.19 hour average error, supporting real-time low-latency applications.
The cumulative cost of additional wakefulness: dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation
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Toward Real-Time Circadian Phase Estimation with Low Latency from Wearable Sensing Data
Machine learning models estimate circadian phase from about 8 hours of light and activity wearable data with 1.19 hour average error, supporting real-time low-latency applications.