Signal processing
PPG-Based Sleep Staging Algorithms
PPG-based sleep staging classifies sleep into wake, light (N1/N2), deep (N3), and REM stages using heart rate dynamics, HRV spectral changes, respiratory rate modulation, and accelerometer-derived movement patterns.
How it works
Schematic summary of this guide. Waveforms are illustrative, not measured data.
Each sleep stage produces characteristic autonomic signatures detectable in PPG. Deep sleep (N3) shows the lowest heart rate, highest HRV (RMSSD), and most prominent respiratory sinus arrhythmia. REM sleep increases heart rate variability with sympathetic bursts and irregular respiratory patterns. Light sleep (N1/N2) shows intermediate values. Wake periods exhibit higher heart rate, reduced HRV, and increased movement.
Machine learning classifiers extract features from 30-second epochs matching PSG scoring convention. Features include: mean HR, RMSSD, LF/HF ratio, respiratory rate, respiratory amplitude variability, body movement count, and movement intensity from accelerometer.
Frequently Asked Questions
How accurate is wearable sleep staging compared to polysomnography?
Moderately. In a 53-adult polysomnography study (Miller et al. 2022, doi:10.3390/s22166317), four-stage epoch agreement ranged from 50% (Garmin Forerunner 245) to 61% (Oura Gen 2) and 65% (Somfit), while sleep-vs-wake agreement was 86–89%. In 62 adults, Schyvens et al. (2025, doi:10.1093/sleepadvances/zpaf021) found Cohen's kappa of 0.21 to 0.53 across six wrist devices. Errors are largest for distinguishing stages rather than detecting sleep.
Why is deep sleep hardest to detect from PPG?
Autonomic features during deep sleep overlap with relaxed wakefulness. Movement-based features cannot differentiate deep sleep from quiet wake or light sleep.
Can PPG-based sleep staging detect sleep disorders?
PPG sleep staging can flag abnormal sleep architecture (reduced deep sleep, fragmented REM) that may indicate sleep disorders. However, it cannot diagnose conditions like narcolepsy or REM behavior disorder that require EEG-based staging.