Internal Joint State Monitoring Using Bio-Inspired Measurement Model for Robotic-Assisted Sit-to-Stand (RA-STS) Training

This article presents a bio-inspired measurement model for the internal force and torque monitoring of human joints, which serves as the foundation of a robotic-assisted sit-to-stand (RA-STS) system consisting of an STS mechanism (STSM) and a lower extremity exoskeleton (LEE). This system is developed for stroke patients to train normal-like body transfer in early rehabilitation. With the sliding/rolling effects of the bio-joints in mind, the human knee joint and ankle joint are modeled as a double-ellipse joint and a double-circle joint, respectively, in the measurement model. The efficiency and accuracy of the measurement models are experimentally validated and demonstrated by comparing them with the traditional multirod-hinge model. Compared to the multirod-hinge model, the estimation accuracy of the internal human joint states (joint motions and joint forces/torques) using the measurement model is increased by 18.0%–72.5% and 32.8%–52.3%, respectively, which will benefit the design of rehabilitation devices. Meanwhile, the effectiveness of the RA-STS system is experimentally evaluated using the measurement model by comparing the effects of six different exercise scenarios (considering both with/without STSM and active/passive LEE) on human joint forces/torques.