Measurement Accuracy

Methods

Systematic review of 45 consumer wearable validation studies

Key Findings

• PPG-derived RMSSD averages 6-11% lower than ECG measurements
• Correlation with ECG remains strong (r > 0.9) for most devices
• Only 13 of 45 devices reviewed had FDA approval
• Motion artifacts remain the biggest accuracy challenge

Limitations

Studies used different protocols, making direct comparison difficult

Methods

Analysis of continuous HRV data from Oura Ring users over multiple weeks

Key Findings

• 5+ nights of data needed for reliable HRV-CV estimation
• Higher HRV-CV associated with alcohol consumption
• Higher HRV-CV linked to lower physical activity levels
• Higher HRV-CV correlated with inconsistent sleep schedules

Limitations

Observational data, correlation not causation

Methods

Scoping review of HRV methodology literature

Key Findings

• LF power reflects both sympathetic and parasympathetic activity
• Breathing rate significantly affects LF/HF independent of autonomic state
• No consensus on interpretation standards
• RMSSD and HF power are more reliable parasympathetic markers

Limitations

Some researchers still defend LF/HF utility in specific contexts

Methods

13 healthy adults, simultaneous ECG reference and multiple wearables during sleep, 536 total nights

Key Findings

• Oura Gen 4: 99% concordance (CCC), 6% mean error for HRV
• Oura Gen 3: 97% concordance, 7% mean error
• Whoop 4.0: 94% concordance, 8% mean error
• Garmin Fenix 6: 87% concordance, 10.5% mean error
• Polar Grit X Pro: 82% concordance, 16% mean error

Limitations

Small sample size, only nocturnal measurements, Oura accuracy decreased at HRV above 60ms

Methods

Joint European Society of Cardiology and North American Society of Pacing and Electrophysiology task force

Key Findings

• Defined time domain measures: SDNN, RMSSD, pNN50
• Defined frequency domain measures: VLF, LF, HF
• Established 5-minute short-term and 24-hour recording standards
• Created framework for clinical and research applications

Limitations

Published before wearable technology era

Methods

Polysomnography study measuring HRV reliability across sleep stages

Key Findings

• High-frequency HRV reliable across N2, deep sleep, and REM
• Correlations ranged from r=0.70 to r=0.88 across stages
• Reliability maintained even during disrupted sleep
• Supports overnight HRV as valid health metric

Limitations

Lab-based study may differ from home monitoring