Koji Makino, Masahiro Nakamura, Hidenori Omori, Yoshinobu Hanagata, Shohei Ueda, Kyosuke Nakagawa, Kazuyoshi Ishida and Hidetsugu Terada. Evaluation Method of the Gait Motion Based on Self-organizing Map Using the Gravity Center Fluctuation on the Sole. International Journal of Automation and Computing, vol. 14, no. 5, pp. 603-614, 2017. DOI: 10.1007/s11633-016-1045-8
 Citation: Koji Makino, Masahiro Nakamura, Hidenori Omori, Yoshinobu Hanagata, Shohei Ueda, Kyosuke Nakagawa, Kazuyoshi Ishida and Hidetsugu Terada. Evaluation Method of the Gait Motion Based on Self-organizing Map Using the Gravity Center Fluctuation on the Sole. International Journal of Automation and Computing, vol. 14, no. 5, pp. 603-614, 2017. DOI: 10.1007/s11633-016-1045-8

# Evaluation Method of the Gait Motion Based on Self-organizing Map Using the Gravity Center Fluctuation on the Sole

• This paper describes the evaluation method of the gait motion in walk rehabilitation. We assume that the evaluation consists of the classification of the measured data and the prediction of the feature of the gait motion. The method may enable a doctor and a physical therapist to recognize the condition of the patients more easily, and increase the motivation of patient further for rehabilitation. However, it is difficult to divide the gait motion into discrete categories, since the gait motion continuously changes and does not have the clear boundaries. Therefore, the self-organizing map (SOM) that is able to arrange the continuous data on the almost continuous map is employed in order to classify them. And, the feature of the gait motion is predicted by the classification. In this study, we adopt the gravity-center fluctuation (GCF) on the sole as the measured data. First, it is shown that the pattern of the GCF that is obtained by our developed measurement system includes the feature of the gait motion. Secondly, the relation between the pattern of the GCF and the feature of the gait motion that the doctor and the physical therapist evaluate by visual inspection is considered using the SOM. Next, we describe the prediction of following features measured by numerical values:the length of stride, the velocity of walk and the difference of steps that are important for the doctor and the physical therapist to make a diagnosis of the condition of the gait motion in walk rehabilitation. Finally, it is investigated that the position of a new test data that is arranged on the map accords with the prediction. As a consequence, we confirm that the method using the SOM is often useful to classify and predict the condition of the patient.

### Catalog

/

DownLoad:  Full-Size Img  PowerPoint