Development of a muscle circumference sensor to estimate torque of the human elbow joint

Abstract

Many researchers are currently studying and developing various kinds of human–robot systems, as this field requires more accurate and reliable sensing systems to detect the intention behind human motion. This study describes a muscle circumference sensor (MCRS) that was developed to measure the variation in the outline of a muscle as a human–robot interface (HRI), as well as an elbow-joint model to develop an estimation algorithm for human elbow-joint torque. A modular-type MCRS and calibration algorithm were developed to measure the muscle-activation signal, which is represented by the normalization of the calibrated MCRS signal. A Hill-type model was applied to the muscle-activation signal, and the kinematic model of the muscle could be used to estimate the joint torques. Experiments were carried out to evaluate the performance of the proposed algorithm using isotonic contraction motion and KIN-COM® equipment under 5Nm, 10Nm, and 15Nm loads. The algorithm and its feasibility for use as an HRI were verified by comparing the joint load condition and the torque estimated using the algorithm.