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JRM Vol.32 No.5 pp. 947-957
doi: 10.20965/jrm.2020.p0947
(2020)

Paper:

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Study on Human Behavior Classification by Using High-Performance Shoes Equipped with Pneumatic Actuators

Yasuhiro Hayakawa*, Yuta Kimata**, and Keisuke Kida**

*Department of Control Engineering, National Institute of Technology, Nara College
22 Yata-cho, Yamatokoriyama, Nara 639-1058, Japan

**Advanced Mechanical Engineering Course, National Institute of Technology, Nara College
22 Yata-cho, Yamatokoriyama, Nara 639-1058, Japan

Received:
March 30, 2020
Accepted:
June 29, 2020
Published:
October 20, 2020
Creative Commons License
Keywords:
pneumatics, supervised machine-learning classifiers, rehabilitation, walking training, shoes
Abstract

In Japan, accidents involving the falling of elderly people are increasingly becoming a problem. To solve this problem, walking training is effective for preventing falls of elderly people. In this study, a walking training system was developed in which high-performance shoes are used to improve the efficiency of walking training. The high-performance shoes have three functions: 1) measurement of plantar pressure using changes in the inner pressure of the insole, 2) leg movement measurement using a six-axis motion sensor, and 3) applying stimulus to the sole of the foot by changing the shape of the insole. A unique rubber element was developed for these functions. Furthermore, a system to predict the behavior of patients during walking training was developed. Based on experimental results, four types of behavior of patients during walking training were predicted. Moreover, leave-one-person-out cross validation was performed by the random forest (RF) machine-learning algorithm, and the F-measure was calculated. As a result, the four types of behavior were classified with an F-measure of 78.6%.

The shoes and dedicated insole elements

The shoes and dedicated insole elements

Cite this article as:
Y. Hayakawa, Y. Kimata, and K. Kida, “Study on Human Behavior Classification by Using High-Performance Shoes Equipped with Pneumatic Actuators,” J. Robot. Mechatron., Vol.32 No.5, pp. 947-957, 2020.
Data files:
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Last updated on May. 08, 2025