Resumen
Aiming at stroke patients? hand rehabilitation training, we present a hand exoskeleton with both active and passive control modes for neural rehabilitation. The exoskeleton control system is designed as a human?robot interaction control system based on field-programmable gate array (FPGA) and Android mobile terminal with good portability and openness. Passive rehabilitation pattern based on proportional derivative (PD) inverse dynamic control method and active rehabilitation pattern based on impedance method, are established respectively. By the comparison of the threshold value and the force on the fingertip of the exoskeleton from the sensor, the automatic switch between active and passive rehabilitation mode is accomplished. The hand model is built in Android environment that can synchronize the movement of the hand. It can also induce patients to participate in rehabilitation training actively. To verify the proposed control approach, we set up and conduct an experiment to do the passive rehabilitation mode, active rehabilitation mode, and active plus passive mode experimental researches. The experiment results effectively verify the feasibility of the exoskeleton system fulfilling the proposed control strategy.