Running-specific prostheses are widely used in Paralympic sport and their performance assessment under real running conditions requires wearable monitoring systems capable of capturing both prosthesis dynamics and athlete kinematics. Existing solutions have been validated in laboratory settings and short trials, leaving open challenges related to autonomy, robustness, and applicability to prolong outdoor running. This study aimed to design and evaluate a wearable IMU-based monitoring system for assessing prosthesis dynamics and athlete kinematics during long-distance running. Four IMU sensors mounted on prosthetic blades and sockets were deployed, addressing practical constraints of battery life, memory, and outdoor robustness. The system was tested during a 35 km trail running race by a former Paralympic athlete with bilateral transtibial amputation. The race course was segmented into nine slope-based sectors, and stride-level metrics, including impact acceleration, vibration peak, damping ratio, and damped natural frequency, were extracted from blade-mounted IMU data and compared across sectors using non-parametric statistics and effect size measures. The results suggest that the proposed system may capture meaningful variations in prosthesis dynamics across different running conditions, with moderate to large effect sizes observed for most metrics. These preliminary findings support the feasibility of the proposed approach for in-field prosthesis monitoring.
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Chicca et al. (2026) studied this question.
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