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 national human activity pattern survey (nhaps): a resource for assessing exposure to environmental pollutants
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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.