Abstract des Autors

Sprint running velocity is the product of step length and step rate. A tool to measure these key metrics would aid sprint training. Athletes require fast and non-invasive analysis tools, to allow them to focus on performance. A non-invasive, single camera gait analysis system (Gait Analyser) was developed and installed at the Sheffield Hallam University City Athletics Stadium (SHUCAS). The Gait Analyser filmed athletes sprinting in lanes 1, 5 and 8 wearing different coloured shoes in varied lighting conditions (e.g. sunlight or overcast). The Gait Analyser automatically identified the position and time of athlete’s foot contacts, allowing the calculation of step length, step time and step velocity. Output data were compared to corresponding, manually identified measurements. For optimised setups, 100% of foot contacts were identified. Resultant direction root-mean square error (RMSE) for foot contact position and time was 108.9 mm and 0.03 s respectively. RMSE for step length, step time and step velocity was 4.9 mm, 0.00 s and 0.07 m·s-1 respectively. The Gait Analyser measured spatio-temporal gait parameters of sprint running in situ without applying markers or sensors to the athlete or the running track: results were available 2-3 s after capture.