日本機械学会論文集
Online ISSN : 2187-9761
ISSN-L : 2187-9761
ロボティクス研究の最前線(第20回ロボティクスシンポジア特集号)
実映像と筋活動の重畳表示によるローイング動作教育システム
Qi AN柳井 香史朗中川 純希温 文山川 博司山下 淳淺間 一
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2016 年 82 巻 834 号 p. 15-00424

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In many sports, essential skills exist in terms of muscle activation in order to improve performance. However, it is difficult to identify the important muscle activation, and moreover novices cannot observe and imitate it since muscle activation is hardly visible. This study especially focuses on human rowing motion to extract an important skill in terms of muscle activation and we develop skill education system for novices to learn the skill. Firstly, strength and activation timing of lower leg muscle are evaluated to detect the expert skill based on their peak value and cross correlation during movement. Next, new skill education system is suggested by simultaneous presentation of real human movement and muscle activations of the targeted muscle. In the proposed system, muscle color is continuously changed based on its activation level for novices to perceive their muscle activation visually. Both experts and novices participated at our skill extraction experiment to compare their muscle activation. Results showed that experts had larger peak activation level and different profile in rectus femoris muscle. Therefore, our skill education system focused on rectus femoris muscle to present its activation level and movement simultaneously. In order to evaluate efficacy of the developed system, four different education instructions were conducted to novices; linguistic education, simultaneous presentation of motion and muscle activation of the expert, off-line presentation of novice's motion and muscle activation, and real time presentation of novice's motion and muscle activation. Performance of novices was evaluated after each instruction based on peak activation level, cross correlation, and exerted power on the rowing ergometer. These performance change after each education implied providing integrated view of novice's motion and muscle activation in real-time could improve performance of rowing motion.

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