Rehabilitation Hand Exoskeleton Robot based on Soft Actuator and Adaptive Control
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Every year, millions of people suffer from severe motor impairment in the hand as a result of strokes or spinal cord injuries, which hinders their ability to perform simple daily activities. However, conventional rigid robots still face significant challenges related to their heavy weight and anatomical incompatibility with human joints, limiting their effectiveness in home-based rehabilitation. This research proposes a solution based on soft pneumatic actuators, Expansive Bending pneumatic actuators muscle (EBPAM) characterized by light weight and high flexibility. The methodology involves designing an intelligent control system that begins with fuzzy logic to track the therapist’s finger movements, and was subsequently developed using an Adaptive Fuzzy Neural Inference System (ANFIS) to compensate for the non-linearity of pneumatic systems. Experimental results demonstrated the system’s ability to achieve accurate motion tracking, with ANFIS successfully reducing tracking error by up to 50% compared to conventional control, whilst maintaining a total glove weight of less than 100 grams, making it ideal for domestic and clinical use.
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