AUTHOR=Carrier Bryson , Melvin Amanda C. , Outwin Jacob R. , Wasserman Marni G. , Audet Adam P. , Soldes Katherine C. , Kozloff Kenneth M. , Lepley Adam S. 

TITLE=Wearables for health monitoring: body composition estimates of commercial smartwatch and clinical bioelectrical impedance device

JOURNAL=Frontiers in Sports and Active Living

VOLUME=Volume 7 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/sports-and-active-living/articles/10.3389/fspor.2025.1644082

DOI=10.3389/fspor.2025.1644082

ISSN=2624-9367

ABSTRACT=IntroductionBody composition is a critical health measure. Accurate monitoring of body composition, such as body fat percentage (BF%) and skeletal muscle mass percentage (SM%), enables individuals to make informed decisions regarding nutrition, exercise, health status and management. Recent advancements have integrated bioelectrical impedance analysis (BIA) into wearable technology, presenting accessible options for tracking body composition measures. However, the validity of wearable BIA devices in comparison to criterion methods remains underexplored. Therefore, this study aimed to assess the validity of a wrist-worn consumer device and a clinical BIA device against the criterion measure of dual-energy x-ray absorptiometry (DXA).MethodsThis study included 108 physically active participants (56 females, 52 males). Participants underwent assessments using DXA, a wearable smartwatch BIA device (wearable-BIA; Samsung Galaxy Watch5), and a clinical standing hand-to-foot BIA analyzer (clinical-BIA; InBody 770). Measures of interest included BF% and SM%. Data were analyzed for accuracy using tests of error [mean absolute error [MAE], mean absolute percentage error [MAPE]], linearity (Pearson's r, Deming regression), agreement (Lin's CCC), and equivalence, complemented by Bland-Altman plots to visually represent bias.ResultsWhen assessing BF%, both the wearable-BIA (r = 0.93; CCC = 0.91) and clinical-BIA (r = 0.96; CCC = 0.86), demonstrated very strong correlations and agreement compared to DXA, with MAPEs of 14.3% and 21.1%, respectively. Female participants using the wearable-BIA device showed the greatest accuracy for BF% (CCC = 0.91, MAPE = 9.19%, equivalence supported). Bland-Altman analysis revealed proportional bias, particularly in individuals with higher BF%. Although correlations were considered strong for SM%, agreement was classified as weak (wearable-BIA: r = 0.92, CCC = 0.45; MAPE = 20.3%; clinical-BIA, r = 0.89; CCC = 0.25; MAPE = 36.1%).DiscussionBoth the wearable- and clinical-BIA device revealed mixed validity, demonstrating strong correlations for both BF% and SM%, and high levels of agreement and low error for BF%. Additionally, the wearable-BIA demonstrated acceptable accuracy for estimating BF% in females. However, wider limits of agreement and variability suggest limitations in validity, particularly for skeletal muscle mass and in individuals with higher body fat percentages. These findings support the practical use of wearable devices for general body composition monitoring when laboratory-based methods are unavailable, though caution is warranted. Continued development and validation efforts are recommended to enhance accuracy and consistency across diverse populations and measures.