Evaluation of a Wearable Hydration Monitor for Estimating Sweat Loss and Hydration Status in Collegiate Athletes: A Pilot Study

Background/Objective: Instantaneous, accurate assessment of hydration and sweat loss has potential to optimize athlete performance and reduce risks associated with excessive exercise-related fluid loss. Reusable wearable hydration monitors, such as hDrop monitors, are an emerging non-invasive, quick, and easy to use alternative to existing methods. Purpose: To assess the accuracy of the hDrop wearable sweat monitors for estimating sweat loss and hydration status compared to established field-based measures, including body mass change and urine indices. Methods: Division I male collegiate soccer athletes contributed repeated training-session observations (38 total observations; 18 complete observations for sweat-loss analyses and 36 for hydration-score–USG analyses). They completed training sessions during which pre- and post-exercise body mass, fluid intake, urine output, and urine samples were collected. Sweat loss was calculated using changes in body mass adjusted for fluid balance. hDrop-derived estimates of sweat loss and hydration status were compared to criterion measures using mean bias, percent of criterion, mean absolute percent error (MAPE), repeated-measures Bland–Altman analysis, and generalized estimating equations accounting for observations clustered within athletes. Associations between hydration scores and urine-based markers were assessed using generalized estimating equations accounting for observations clustered within athletes. Results: The hDrop generated a sweat-loss estimate for 18 of 38 training-session observations (47.4%). Repeated-measures mean bias for sweat loss was −0.423 L (95% CI −1.106 to 0.259 L). The hDrop estimates averaged 106.2 ± 64.8% of criterion while MAPE was 50.3%, reflecting large individual error. In the repeated-measures analysis, criterion-measured sweat loss was positively associated with hDrop-estimated sweat loss (B = 0.204, 95% CI 0.018 to 0.391, p = 0.032). Significant proportional bias was present (slope = −0.790, 95% CI −1.438 to −0.143, p = 0.020), indicating greater underestimation at higher sweat-loss values. In repeated-measures GEE analyses, USG was not significantly associated with the hDrop hydration score either before practice (B = −407.9, 95% CI −1008.7 to 192.8, p = 0.183) or after practice (B = −135.0, 95% CI −803.8 to 533.7, p = 0.692). Conclusions: The hDrop generated sweat-loss estimates in fewer than half of training-session observations and demonstrated substantial individual-level error and significant proportional bias when estimates were available. Although the instantaneous hydration score decreased following exercise, its lack of association with USG leaves its physiological meaning and criterion validity uncertain. These findings do not support use of the hDrop as an interchangeable substitute for established methods of individualized sweat-loss or hydration assessment.