ArticleFrontiers in sports and active living2025
Wearables for health monitoring: body composition estimates of commercial smartwatch and clinical bioelectrical impedance device.
Article in Frontiers in sports and active living, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Consumer Smartwatch Technology in Health and Performance Research: Validity, Limitations, and Real-World Applications.Sensors (Basel, Switzerland) · 2026Review
- Advancing sarcopenia assessment with wearable and app-based technology: a scoping review.The journal of nutrition, health & aging · 2026Article
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Authors and funding
8 authors.
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Abstract
Introduction: Body 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). Methods: This 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 Results: When assessing BF%, both the wearable-BIA ( Discussion: Both 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.
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