Feature

Sleep Tracking

Automatic detection and analysis of sleep periods, tracking duration, timing, and quality metrics. Sleep tracking typically uses accelerometer-based movement detection combined with heart rate patterns to identify sleep onset and wake times, eliminating manual logging. Key metrics include total sleep time, time in bed, sleep efficiency (time asleep / time in bed), sleep latency (time to fall asleep), and wake episodes. Many devices calculate composite sleep scores integrating multiple factors. Consistent sleep timing (low variability in bedtime and wake time) is associated with better health outcomes independent of duration. The circadian alignment of sleep—sleeping during biological night—affects sleep quality and metabolic health. Sleep debt from chronic insufficient sleep accumulates and requires multiple recovery nights to resolve. Wearables help users understand sleep patterns, identify improvement opportunities (earlier bedtime, reduced evening screen time, consistent schedule), and correlate sleep with next-day energy and performance. Accuracy for total sleep time is generally within 30 minutes of PSG; efficiency and wake detection are less accurate.

0 devices with this feature