Abstract
This paper describes an estimation method for the physical parameters of human arms. The parameters are used in the medical and kinematic analysis fields. Personal differences are important, but some of the conventional methods do not consider personal differences pertaining to inertia in viscoelasticity muscular strength measurements. The remaining conventional methods that consider personal differences require precise measurement devices. The proposed method realizes kinetics modeling and identification of the friction and inertia including the off-diagonal parameters of human arms by using wearable robots. First, wearable robots are multi-input devices. In addition, the actuators of wearable robots can be located near human joints and can input M-sequence torque. Therefore, wearable robots can input signals having a high signal-to-noise ratio and ensuring persistently exciting characteristics in each human joint. By employing multi-input characteristics, the proposed method can reduce patients' burden by shortening the amount of time for estimation. In addition, we verify the accuracy of the estimated parameters by comparing the responses of the actual machine with those obtained by simulation.
