Estimation Method of Turn Section During Swimming by Using Ensemble Learning and Single Inertial Sensor

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  • KOBAYASHI Masahiro
    Department of Information and Management Systems Engineering, Nagaoka University of Technology
  • SAKAI Kazuki
    Department of Electronic Control Engineering, National Institute of Technology, Nagaoka College
  • OMAE Yuto
    Department of Electrical Engineering, National Institute of Technology, Tokyo College
  • AKIDUKI Takuma
    Department of Mechanical Engineering, Toyohashi University of Technology
  • SHIONOYA Akira
    Department of Information and Management Systems Engineering, Nagaoka University of Technology
  • TAKAHASHI Hirotaka
    Department of Information and Management Systems Engineering, Nagaoka University of Technology

Bibliographic Information

Other Title
  • 単一慣性センサとアンサンブル学習を活用した競泳中のターン区間推定
  • タンイツ カンセイ センサ ト アンサンブル ガクシュウ オ カツヨウ シタ キョウエイ チュウ ノ ターン クカン スイテイ
Published
2019-02-15
Resource Type
journal article
DOI
  • 10.3156/jsoft.31.1_597
Publisher
Japan Society for Fuzzy Theory and Intelligent Informatics

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Description

<p>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.</p>

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