Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : June 01, 2022 - June 04, 2022
In this paper, we propose to develop a handrail with pressure sensors and load cells in order to estimate the posture of griping the handrail and the grip strength. Eleven healthy male participants gripped the developed handrail in two situations. As a result of classifying the posture of grasping the handrail using SVM, the postures of griping the handrail can be identified with high probability. Grip strength was estimated using several machine learning methods. The gradient boosting method showed the best accuracy and the possibility of detecting approximately 4-kg decrease of muscle strength at least.