Online Monitoring of Swimmer Training Using a 3D Accelerometer Identifying Swimming and Swimming Style

摘要

In the process of optimizing training efficiency and improving results of the athletes, technology has increasing share. Wearable sensors, especially those measuring motion are lately acquiring more and more interest. In this paper, we aimed to develop online monitoring tool of swimming training, more in particular algorithm for detection of swimming and turning events using 3D accelerometer. Additionally, algorithm should be able to discriminate between performed swimming styles. This study included data of 10 swimmers who swam on predefined protocol for 1200m. Each swimmer was equipped with wireless waterproof 3D accelerometer attached over right wrist. Algorithm showed high accuracy of 100% for detection of swimming and turning activity. Additionally, detection of swimming styles such as crawl, breaststroke and backstroke resulted of 100% true positive rate. However, true positive rate decreased to 95% for detection of butterfly event. To conclude, we demonstrate that swimming activity together with style recognition can be registered using wireless waterproof 3D accelerometer. Furthermore, we show that such detection can be automatized and performed in an online mode. Taken together, this development leads to a useful online monitoring tool of swimming training.