Evaluation of Exertional Sweat Loss Estimates in Wearable Technology

Clinical Snapshot

Key Findings

• P Value: Not reported in abstract

• Effect Size: Acceptable correlation (CCC 0.71-0.90) but substantial errors (MAPE 25.38-33.21%)

• Primary Outcome: Accuracy of smartwatch sweat loss estimates compared to gold standard body mass change

• Nnt Or Sensitivity: Mean absolute percentage error 25.38-33.21% indicating poor precision for clinical use

• Confidence Interval: Confidence intervals provided for difference in means (specific values not reported in abstract)

Clinical Application

High feasibility for general population monitoring but limited utility for precise clinical hydration management Relevant for Australian sports medicine practitioners and exercise physiologists, particularly given high participation in outdoor running activities and extreme climate conditions requiring hydration monitoring Active adults engaged in endurance exercise, particularly runners across various fitness levels and environmental conditions

Abstract

BACKGROUND: Wearable technology shows promise for monitoring exertional sweat loss, yet its accuracy requires evaluation. This study evaluated the accuracy of 2 commercially available smartwatches for estimating sweat loss compared with gold standard methods. HYPOTHESIS: Sweat loss values measured via wearable technology will be determined accurate compared with gold standard methods. STUDY DESIGN: Cross-sectional. LEVEL OF EVIDENCE: Level 2. METHODS: A total of 111 participants (age, 40 ± 14 years; height, 171.0 ± 8.9 cm; body mass, 70.8 ± 14.7 kg; VO2max, 46.8 ± 8.7 ml/kg/min) completed up to 4 running trials under varying conditions (indoor/outdoor, distances from 2.5 km to 20 km, and interval runs). Sweat loss estimates from each smartwatch were compared with criterion measurements based on change in nude body mass pre- and postexercise. Validity statistics included tests for error (mean absolute error [MAE], mean absolute percentage error [MAPE]), linearity (Lin's concordance correlation coefficient [CCC], Pearson's [r], and Deming regression), equivalence (CI for difference in means), and Bland-Altman plots for bias assessment. Stratified analyses by sex, weight, and fitness category were also completed, along with a chi-square test of independence. RESULTS: Both devices demonstrated acceptable overall correlation (CCC range, 0.71 to 0.90) but substantial errors in estimating exertional sweat loss (MAPE range, 25.38% to 33.21%). Stratified analyses yielded similar results, with no additional analyses meeting the combined validity thresholds. CONCLUSION: Wearable devices offer a promising and convenient tool for general sweat loss tracking but lack the precision to replace laboratory methods for hydration management. Traditional methods remain essential for the most accurate measurements. CLINICAL RELEVANCE: Wearable devices provide an accessible option for sweat loss monitoring. This study highlights their potential for general tracking while emphasizing the need for laboratory methods when accuracy is critical, ensuring better guidance for hydration strategies in sports performance and health applications.

References

1. 1.Carrier, B., Melvin, A. C., Outwin, J. R., Wasserman, M. G., Audet, A. P., Soldes, K. C., Kozloff, K. M., & Lepley, A. S. (2026). Evaluation of exertional sweat loss estimates in wearable technology. Sports Health. https://doi.org/10.1177/19417381251388642