Rehabilitation Path Planning Based on Human Motion Output and Ergonomic Index Optimization

• Published in: Data Driven Control and Learning Systems Conference (Online) pp. 567 - 572
• Main Authors: He, Tianyu, Yan, Yangben, Wang, Gang, Liu, Yongbai, Liu, Keping, Sun, Zhongbo
• Format: Conference Proceeding
• Language: English
• Published: IEEE 03.08.2022
• Subjects: Assistive robots; Ergonomic Index; Ergonomics; Fitting; Golden Section Algorithm; Learning systems; Motion capture; Path planning; Rehabilitation Path Planning; Standardized Output Function; Training
• ISSN: 2767-9861
• DOI: 10.1109/DDCLS55054.2022.9858384

Rehabilitation robots help patients perform rehabilitation training according to the planned path, and reasonable planning of the rehabilitation path can enable patients to obtain better rehabilitation effects. In view of the problems of low degree of personification and poor comfort in the path planning of rehabilitation robots. In this paper, the normalized output function for human-like path planning is obtained, which is based on the inherent virtual constraints or output of the human lower limb, and the constraints are optimized through ergonomic index. First, the human body output data of the subject is collected through the optical motion capture system, after that the original normalized output function is obtained by Fourier fitting, and then the constraints are based on ergonomic indicators. Second, the constrained human body output data is calculated by the golden section algorithm, and finally the final human body standardized output function is obtained by Fourier fitting. Last, the standardized output function based on human output is applied in the path planning of rehabilitation robots, which can make the training of rehabilitation robots have a higher degree of human simulation and comfort, so as to achieve better rehabilitation effect.