2019 Volume 31 Issue 1 Pages 597-602
We aim to develop a swimming motion coaching system for beginner and/or intermediate swimmers using a single inertial sensor. One of the requirements of the system is the process of automatically estimating and dividing the section of swimming motions (such as stroke and turn) from the sensor data. In the previous study which performed automatic estimation of the swimming motion by non ensemble learning, it was impossible to remove the different motion patterns by individuals, and the generalization ability was low. In this paper, in order to learn a common pattern in each motion and realize the motion estimation with high accuracy, we proposed an estimation method of the turn section by using random forest which is one of ensemble learning. As a result, it was suggested that the turn section could be estimated with higher accuracy than non ensemble learning method in all four swimming styles.