Prediction of Sit-to-Stand Time Using Trunk Angle and Lower Limb EMG for Assistance System

Abstract

Herein, we propose a method to predict the sit-to-stand time of a user movement assist system. The proposed method predicts the sit-to-stand time using changes in the trunk angle and lower limb muscle activity, based on multiple regression analysis. To verify the accuracy of the proposed method and evaluate data regarding various standing speeds, we conducted experiments on nine participants. The evaluation results show that the proposed method reduced the average error by approximately 35.6% when compared to the conventional method.