Researchwearablesvo2maxmlmeta analysis
Wearable Data Predicts Cardiorespiratory Fitness Accurately
7.1
A systematic review and meta-analysis (search through July 27, 2024) evaluated models estimating cardiorespiratory fitness (CRF) from continuous free-living wearable data, including 18 studies and 31,072 participants. The pooled correlation between predicted and measured CRF was 0.83 (95% CI 0.77–0.88), but heterogeneity was high (I2=97%) and most studies lacked external validation, limiting immediate clinical adoption.
Key Points
- 1Reported pooled correlation of 0.83 between wearable-predicted CRF and measured values across 18 studies.
- 2Highlighted high heterogeneity (I2=97%) and common bias in data analysis and handling methods.
- 3Indicated need for external validation and standardized pipelines before clinical adoption of wearable CRF models.
Scoring Rationale
Solid pooled evidence and clinical relevance, tempered by very high heterogeneity and lack of external validation.
Sources
Public references used for this report.
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