Evaluation of Assistance System to Predict Sit-to-stand Speed using Trunk Angle and Lower Limb EMG

Abstract

We have developed a sit-to-stand assist system that predicts the movement speed and drives at that speed. The assistance system predicts the speed of sit-to-stand movement based on multiple regression analysis. The measurement of trunk angle and lower limb electromyogram (EMG) were used as the explanatory variables for the multiple regression analysis. To verify the effectiveness of the developed system, we conducted evaluation experiments on two participants. The evaluation was performed based on the difference of amount of system support between the conventional constant speed control and the proposed predictive speed control. The evaluation results show that the predictive speed control resulted in more support, confirming the effectiveness of the system control that predicted the sit-to-stand speed.