Validation of a Low-Cost Accelerometry Device for Cycle-Based Biomechanical Analysis of Deep-Water Running

Hydrotherapy is widely used in rehabilitation because it reduces mechanical loading while preserving neuromuscular and cardiovascular stimulation. However, the biomechanical characterization of deep-water running remains limited, particularly when using accessible wearable systems for cycle-based movement analysis. This study aimed to evaluate the concurrent validity and agreement of a low-cost accelerometry device for cycle-based analysis of deep-water running, using a commercial accelerometry system as the reference measurement system. Twenty-one healthy participants performed a 25 m deep-water running task with simultaneous data acquisition from mechanically coupled sensors to ensure alignment. A total of 75 synchronized cycles were processed using a standardized pipeline that included filtering, synchronization, cycle detection, and parameter extraction. Statistical analysis was conducted using the Wilcoxon signed-rank test, intraclass correlation coefficient, Spearman’s correlation, Bland–Altman analysis, and error metrics. The results showed good agreement for temporal and volumetric variables, including cycle duration (ICC = 0.84), cumulative acceleration (ICC = 0.82), and area under the curve (ICC = 0.68). However, lower agreement and systematic bias were observed for intensity-related variables, particularly RMS and peak acceleration, despite more than 92% of cycles falling within the 95% limits of agreement (LoA). These findings suggest that the proposed device provides acceptable agreement for temporal and volumetric variables during deep-water running and may represent a low-cost alternative for movement monitoring in aquatic environments. However, intensity-related variables should be interpreted with caution due to the systematic differences observed between systems.