Prediction of Kick Count in Triathletes during Freestyle Swimming Session Using Inertial Sensor Technology

Abstract

Monitoring sports training performances with automatic, low cost, low power, and ergonomic solutions is a topic of increasing importance in the research of the last years. A parameter of particular interest, which has not been extensively dealt with in a state-of-the-art way, is the count of kicks during swimming training sessions. Coaches and athletes set the training sessions to optimize the kick count and swim stroke rate to acquire velocity and acceleration during swimming. In regard to race distances, counting kicks can influence the athlete’s performance. However, it is difficult to record the kick count without facing some issues about subjective interpretation. In this paper, a new method for kick count is proposed, based on only one triaxial accelerometer worn on the athlete’s ankle. The algorithm was validated on data recorded during freestyle training sessions. An accuracy of 97.5% with a sensitivity of 99.3% was achieved. The proposed method shows good linearity and a slope of 1.01. These results overcome other state-of-the-art methods, proving that this method is a good candidate for a reliable, embedded kick count.