Application of hand rehabilitation device in hemiplegic hand rehabilitation

Statistics show that after stroke, only 15% of patients can recover about half of their hand function, and only 3% of patients can recover more than 70% of their original hand function. It has become a major trend in the rehabilitation field to explore effective rehabilitation treatment methods and promote the recovery of patients' hand function. Therefore, the combination of task-oriented training and emerging rehabilitation technology has gradually become an indispensable rehabilitation treatment technology for hand function rehabilitation. The emergence of hand function rehabilitation robots has brought new ideas for the rehabilitation of hand function after stroke.

This article will briefly share the intelligent soft hand rehabilitation robot and brain-computer interface hand-function robot.

Intelligent soft hand rehabilitation robot

The intelligent soft hand function rehabilitation robot combines robotic technology and neuroscience, and can provide various training modes such as passive, assistance, resistance, bilateral mirror and active games. It is a hand function rehabilitation robot that fully covers the period from soft paralysis to rehabilitation. In the process of robot-assisted training, bilateral mirror therapy and motor imagery were combined to realize the integrated treatment of central intervention and peripheral intervention.

With the intelligent soft hand rehabilitation robot, patients can stimulate the motor cortex of the brain through multi-modal stimulation through visual, auditory and tactile sensory stimulation to form a closed-loop rehabilitation training and improve the patient's willingness to actively participate in hand function rehabilitation training to promote the recovery of the patient's motor function. At the same time, in bilateral mirror therapy, the healthy hand drives the affected hand to exercise, which can further improve the neuroplasticity of the brain.

brain-computer interface hand-function robot

The addition of new methods makes the closed-loop rehabilitation model of central-peripheral-central a clinically important rehabilitation theory. Central intervention can promote the activation of the corresponding functional brain areas of the brain and improve brain neuroplasticity. Peripheral intervention continuously strengthens the positive feedback of sensory and motor control modes to the brain center. The combination of the two modes promotes the remodeling of brain function in stroke patients. The brain-computer interface has become the best choice to realize the closed-loop rehabilitation mode.

Brain-computer interface training will give patients VR visual and auditory dual stimulation, so that they can perform motor imagination of the affected hand movements, so as to control the exoskeleton rehabilitation robot to complete the hand grasping and opening movements. Through brain-computer interface training, patients repeatedly imagine the grasping and opening movements of the affected hand in their brains, and the generation of actual movements assisted by exoskeleton robots achieves a high degree of matching between motor intentions and behavioral movements, which is more conducive to Remodeling of the cerebral cortex.

At present, the brain-computer interface hand function rehabilitation robot has gradually been recognized by patients.

The picture below shows the patient's motor imagination task of hand grasping and opening according to the display screen and voice prompts. Each action has 3 imagination opportunities. While the patient is performing motor imagery, the EEG device can collect the characteristic EEG signals of the cerebral motor cortex through the collector.

If the patient can accurately complete the motor imagery task within 3 times, the EEG signal will complete the signal extraction and feature conversion through the signal converter, and then control the exoskeleton manipulator to help the patient complete the corresponding grasping or opening action; If the motor image cannot be accurately completed within 3 chances, the EEG signal converter cannot be triggered to complete the movement of the exoskeleton manipulator. According to the patient's performance, the system will score the patient's degree of completion, which also improves the patient's enthusiasm for participating in the training.

 However, at present, there are still some problems with hand function rehabilitation robots commonly used in clinical practice. It is hoped that such problems can be improved in future research.