HRV (SDNN), Cardio Fitness (VO₂ max estimate), sleep staging, and AFib detection — how each metric is measured and what the limitations are.
Apple Watch reports HRV as SDNN (standard deviation of all normal RR intervals), not RMSSD like most other wearables. SDNN captures both short-term and long-term heart rate variability, making it higher in absolute value than RMSSD from the same recording period. SDNN and RMSSD are not directly comparable.
Apple calls their VO₂ max estimate "Cardio Fitness." It requires outdoor walking or running with GPS to calculate, using heart rate response to exercise pace. The algorithm received FDA clearance. Accuracy compared to lab VO₂ max: r ≈ 0.78 in validation studies (lower than Garmin's running-based estimate).
Cardio Fitness Levels (Apple's classification):
| Level | Approximate VO₂ Max Range |
|---|---|
| High | Varies by age/sex — upper third of population |
| Above Average | Upper-middle quartile |
| Below Average | Lower-middle quartile |
| Low | Bottom quartile — Apple prompts attention |
Apple Watch detects sleep stages (Awake, REM, Core/Light NREM, Deep NREM) using a combination of accelerometry and heart rate. Accuracy is moderate — comparable to other wrist devices. Deep sleep is frequently underestimated. Sleep data is accessible in the Health app and through third-party apps like AutoSleep.
Apple Watch uses optical PPG to classify rhythm as AFib or sinus rhythm during specific measurement windows. The feature is FDA-cleared for AFib detection in people with known AFib. Sensitivity is approximately 98% and specificity approximately 91% in clinical validation. It does not diagnose AFib — it flags patterns for medical follow-up.
Series 8+ includes a wrist skin temperature sensor measuring deviation from nightly baseline. Uses dual sensors (wrist and back case) to minimize ambient temperature interference. FDA-cleared for cycle tracking (ovulation detection). Also inputs into retrospective ovulation estimates in the Health app.