Using free-living heart rate data as an objective method to assess physical activity: a scoping review and recommendations by the INTERLIVE-network targeting consumer wearables - Schumann, M.; Feuerbacher, J. F.; Heinrich, L.; Olvera-Rojas, M.; Sclafani, A.; Brønd, J. C.; Grøntved, A.; Caulfield, B.; Ekelund, U.; Bloch, W.; Cheng, S.; Sardinha, L. B.; et al. (Sports Medicine, 2025)
Wearable technologies open up new avenues for the assessment of individual physical activity behaviour. Particularly, free-living heart rate (HR) data assessed by optical sensors are becoming widely available. However, while an abundancy of scientific information and guidance exists for the processing of raw acceleration data, no universal recommendations for the utilization of continuous HR recordings during free-living conditions are available. Towards Intelligent Health and Well-Being: Network of Physical Activity Assessment (INTERLIVE®) is a joint European initiative of six universities and one industrial partner. The consortium was founded in 2019 and strives towards developing best-practice recommendations in the context of consumer wearables and smartphones. The aim of this scoping review (following PRISMA-ScR procedures) and recommendations was to provide best-practice protocols for deriving individual physical activity profiles from continuous HR recordings by wearables. The recommendations were developed through an initial scoping review, grey literature searches of promotional material and user manuals of leading wearable manufacturers as well as evidence-informed discussions among the members of the INTERLIVE®-network. The scoping review was performed on the generic domains required for physical activity assessment, namely: (1) `assessment of maximal heart rate`, (2) `determination of basal and/or resting heart rate` and (3) `heart rate-derived intensity zones`, for which we finally included a total of 72, 2 and 11 eligible papers, respectively. Gathering recent knowledge, we provide a decision tree and detailed recommendations for the analysis of free-living HR data to derive individual physical activity profiles. Moreover, we also provide examples of HR-metric calculations that help to illustrate data processing and reporting.