Spinal Cord Injury (SCI) and stroke are two major reasons that cause nervous system damage, and thus lead to paralysis of limbs. Traditional rehabilitation training includes physical therapy, occupational therapy and exercise therapy, which have been proven to have certain effect to the recovery of patients' nervous system. However, the majority of hospitals still carry out the above treatments manually which increases the labor intensity of therapists and causes inadequate training of patients. Rehabilitation robot with its automation, accurate and intelligent features begins to replace therapists to complete some repetitive training tasks, and becomes a new hot spot in robotics. This paper developed two robotic rehabilitation systems, and implemented FES-assisted training strategy, active training strategy for the neurological rehabilitation of SCI or stroke patients. This research is supported in part by the National Hi-Tech R & D Program (863) of China (Grant 2009AA04Z201), the Sci. & Tech. for the Disabled Program of the Chinese Academy of Sciences (Grant KGCX2-YW-618), and the Program of International Sci. & Tech. Cooperation (Grant 2011DFG13390). The main contributions and innovations of this research are as follows: [1] Two robotic rehabilitation systems are developed, which are a functional electrical stimulation (FES) ergometry and a reclining type lower-limb rehabilitation robot. The electrical control and human-machine interaction software for both systems are designed. A functional electrical stimulation system with 8 channels and a surface Electromyography (sEMG) acquisition system with 8 channels are also developed. [2] In order to achieve the power-assisted FES training strategy for the FES ergometry, an iterative learning control-based (ILC) control scheme has been proposed, which successfully addresses the delay and instability characteristics of the FES-induced muscle contraction. By analyzing sEMG and torques signals acquired from health subject during cycling, a stimulation pattern is established and severed as the reference for the ILC. To imitate the healthy contraction pattern of the muscle during cycling, Gluteus Maximus (GM) and Quadriceps Femoris (QF) are applied with FES which is regulated by a P-type ILC. Furthermore, fuzzy logic control is introduced to adjust the proportion gain of the P-type ILC to reduce the number of the iteration, and thus achieves a fast tracking for the desired torques. The experimental results ...
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