Abstract
BACKGROUND: Technological advances have recently made possible the estimation of maximal oxygen consumption (VO(2max)) by consumer wearables. However, the validity of such estimations has not been systematically summarized using meta-analytic methods and there are no standards guiding the validation protocols. OBJECTIVE: The aim was to (1) quantitatively summarize previous studies investigating the validity of the VO(2max) estimated by consumer wearables and (2) provide best-practice recommendations for future validation studies. METHODS: First, we conducted a systematic review and meta-analysis of studies validating the estimation of VO(2max) by wearables. Second, based on the state of knowledge (derived from the systematic review) combined with the expert discussion between the members of the Towards Intelligent Health and Well-Being Network of Physical Activity Assessment (INTERLIVE) consortium, we provided a set of best-practice recommendations for validation protocols. RESULTS: Fourteen validation studies were included in the systematic review and meta-analysis. Meta-analysis results revealed that wearables using resting condition information in their algorithms significantly overestimated VO(2max) (bias 2.17 ml·kg(-1)·min(-1); limits of agreement - 13.07 to 17.41 ml·kg(-1)·min(-1)), while devices using exercise-based information in their algorithms showed a lower systematic and random error (bias - 0.09 ml·kg(-1)·min(-1); limits of agreement - 9.92 to 9.74 ml·kg(-1)·min(-1)). The INTERLIVE consortium proposed six key domains to be considered for validating wearable devices estimating VO(2max), concerning the following: the target population, reference standard, index measure, testing conditions, data processing, and statistical analysis. CONCLUSIONS: Our meta-analysis suggests that the estimations of VO(2max) by wearables that use exercise-based algorithms provide higher accuracy than those based on resting conditions. The exercise-based estimation seems to be optimal for measuring VO(2max) at the population level, yet the estimation error at the individual level is large, and, therefore, for sport/clinical purposes these methods still need improvement. The INTERLIVE network hereby provides best-practice recommendations to be used in future protocols to move towards a more accurate, transparent and comparable validation of VO(2max) derived from wearables. PROSPERO ID: CRD42021246192.