Inertial Sensor and Cluster Analysis for Discriminating Agility Run Technique

Performance in an agility run drill is often used to characterize an athlete's ability to quickly and explosively change direction. Beyond athletic applications, agility tasks are also used to assess the physical readiness of warfighters for battle and the influence that their equipment has on their performance. However, in all of these applications, performance is currently assessed solely by reporting the time it takes to complete the drill. While completion time quite meaningfully discriminates bottom-line performance, it does not reveal the underlying biomechanics that contributes to or limits that performance. Biomechanical metrics that accurately identify performance strengths and weaknesses could promote rapid performance gains via tailored training programs and inform equipment design improvements. To these ends, we propose using a belt-worn wireless inertial measurement unit (IMU) to quantify the biomechanical metrics underlying speed and agility performance in agility assessment tasks. Herein, we describe a drift correction methodology that enables estimates of displacement, velocity, and acceleration of a subject's sacrum provided a course with known waypoints. We demonstrate the utility of this methodology through analysis of a large data set collected from 32 subjects completing a slalom run. A k-means cluster analysis of proposed performance metrics reveals two distinct groups of subjects who use fundamentally different techniques to negotiate the turns of the course. We believe that this measurement methodology can be used widely for agility assessment to provide athletes, trainers and researchers with actionable data to inform training plans and equipment modifications.