Introduction: Biomaterial-enabled wearables (smart-textile ECG garments and skin-conformal/microfluidic sweat patches) are increasingly proposed for athlete monitoring during training and competition. However, field translation remains constrained by sport-specific stressors (e.g. multidirectional motion, high sweat rates, and interface instability) and by inconsistent reporting of signal processing and data quality, sustaining a validity gap from lab to field.
Methods: We performed a targeted evidence map restricted to athletes and training/competition contexts, including primary studies evaluating biomaterial-enabled wearables against an in-use reference during sport tasks. Studies were categorized by device type (smart textiles vs skin-adhesive/microfluidic patches) and classified by validation domain: physiological/biological validity, analytical validation (signal quality, drift, adhesion/washability, data loss), and decision validity (actionable sport endpoints, e.g., thresholds or hydration indices).
Results: Eight studies met the inclusion criteria, including works on smart textiles representing 50.0% (4/8) and skin-adhesive/microfluidic patches representing 50.0% (4/8) (hybrid systems 0%). All studies assessed physiological/biological validity 100% (8/8), typically via agreement against team systems/standard patches/blood lactate or via feasibility of interpretable biosignals during sport tasks. Explicit analytical validation metrics (quantified artefact burden, interface stability under sweat shear, washability, or data-loss rates) were reported in 25.0% (2/8), despite frequent mention of motion/sweat as key limitations. Decision validity was addressed in 37.5% (3/8) through performance- or practice-relevant endpoints, including sweat lactate threshold during swimming and sweat electrolyte/sweat-rate metrics during elite team-sport practice. Across contexts, a recurring field failure mode was degradation of signal interpretability during vigorous, multidirectional movement and prolonged sweating, with limited transparency on preprocessing and artefact handling.
Conclusions: Athlete-context studies show promising physiological agreement, but the dominant gap is field robustness and decision readiness, driven by motion/sweat challenges and under-reporting of analytical and preprocessing details. Standardized artefact reporting and explicit decision-level validation are needed to accelerate reliable adoption in training and competition.
