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Teaching Training Method of a Lower Limb Rehabilitation Robot
Author(s) -
Yongfei Feng,
Hongbo Wang,
Tingting Lu,
Victor Vladareanuv,
Qi Li,
Chaosheng Zhao
Publication year - 2016
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/62445
Subject(s) - computer science , kinematics , rehabilitation , trajectory , physical medicine and rehabilitation , lower limb , training (meteorology) , motion (physics) , acceleration , simulation , artificial intelligence , physical therapy , medicine , surgery , physics , classical mechanics , astronomy , meteorology
This paper presents a new lower limb rehabilitation robot (hereafter, referred to as LLR-Ro) to help patients with lower limb disorder recover their movement function. Based on the ergonomics and kinematics principle, the motion of a human lower limb is analysed, which provides a theoretical basis for the leg mechanism design of LLR-Ro. This paper also proposes a teaching training method for improving the training performance of LLR-Ro. When a physician trains the lower limb of a patient, the acceleration data of the patient's lower limb motion will be collected through a wireless data acquisition system. The data can reproduce the movement trajectory of the physician rehabilitation training and this can be used as the training trajectory of LLR-Ro. The experiment results of this study demonstrate that the teaching training method is feasible. The theory analysis and experimental research of LLR-Ro lay the foundations for the future clinical application of this method

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