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KMID : 1137820170380030129
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의공학회지
2017 Volume.38 No. 3 p.129 ~ p.136
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Gait Type Classification Based on Kinematic Factors of Gait for Exoskeleton Robot Recognitio
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Cho Jae-Hoon
Bong Won-Woo
Kim Dong-Hun
Choi Hyeon-Ki
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Abstract
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The exoskeleton robot is a technology developed to be used in various fields such as military, industry and medical treatment. The exoskeleton robot works by sensing the movement of the wearer. By recognizing the wearer's daily activities, the exoskeleton robot can assist the wearer quickly and efficiently utilize the system. In this study, LDA, QDA, and kNN are used to classify gait types through kinetic data obtained from subjects. Walking was selected from general walking and stair walking which are mainly performed in daily life. Seven IMUs sensors were attached to the subject at the predetermined positions to measure kinematic factors. As a result, LDA was classified as 78.42%, QDA as 86.16%, and kNN as 87.10% ~ 94.49% according to the value of k.
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KEYWORD
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Gait, Exoskeleton robot, Kinematics, IMUs sensor, Machine learning
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