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Journal of Healthcare Engineering
Volume 2017 (2017), Article ID 1523068, 11 pages
https://doi.org/10.1155/2017/1523068
Research Article

Research on Safety and Compliance of a New Lower Limb Rehabilitation Robot

1Parallel Robot and Mechatronic System Laboratory of Hebei Province, Key Laboratory of Advanced Forging & Stamping Technology and Science of Ministry of Education, Yanshan University, Qinhuangdao 066004, China
2Institute of Solid Mechanics of Romanian Academy, 010141 Bucharest, Romania

Correspondence should be addressed to Hongbo Wang

Received 19 March 2017; Revised 16 May 2017; Accepted 7 June 2017; Published 26 July 2017

Academic Editor: Yi-Hung Liu

Copyright © 2017 Yongfei Feng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The lower limb rehabilitation robot is an application of robotic technology for stroke people with lower limb disabilities. A new applicable and effective sitting/lying lower limb rehabilitation robot (LLR-Ro) is proposed, which has the mechanical limit protection, the electrical limit protection, and the software protection to prevent the patient from the secondary damage. Meanwhile, as a new type of the rehabilitation robots, its hip joint rotation ranges are different in the patient sitting training posture and lying training posture. The mechanical leg of the robot has a variable workspace to work in both training postures. So, if the traditional mechanical limit and the electrical limit cannot be used in the hip joint mechanism design, a follow-up limit is first proposed to improve the compatibility of human-machine motion. Besides, to eliminate the accident interaction force between the patient and LLR-Ro in the process of the passive training, an amendment impedance control strategy based on the position control is proposed to improve the compliance of the LLR-Ro. A simulation experiment and an experiment with a participant show that the passive training of LLR-Ro has compliance.