Application de hand rééducation appareil in hémiplégique hand rééducation

Statistics show that after accident vasculaire cérébral, only 15% de patients can récupérer about half de their hand function, and only 3% de patients can récupérer more than 70% de their original hand function. It has become a major trend in le rééducation field to explore efficace rééducation treatment methods and promote le récupération de patients' hand function. Therefore, le combination de task-oriented training and emerging rééducation technologie has gradually become an indispensable rééducation treatment technologie for hand function rééducation. Le emergence de hand function rééducation robots has brought new ideas for le rééducation de hand function after accident vasculaire cérébral.

This article will briefly share le intelligent souple hand rééducation robot and brain-computer interface hand-function robot.

Intelligent souple hand rééducation robot

Le intelligent souple hand function rééducation robot combines robotic technologie and neuroscience, and can provide various training modes such as passive, assistance, resistance, bilateral mirror and active games. It est a hand function rééducation robot that fully covers le period from souple paralysis to rééducation. In le process de robot-assisted training, bilateral mirror thérapie and motor imagery were combined to realize le integrated treatment de central intervention and peripheral intervention.

With le intelligent souple hand rééducation robot, patients can stimulate le motor cortex de le brain through multi-modal stimulation through visual, auditory and tactile sensory stimulation to form a closed-loop rééducation training and améliorer le patient's willingness to actively participate in hand function rééducation training to promote le récupération de le patient's motor function. At le same time, in bilateral mirror thérapie, le healthy hand drives le affected hand to exercise, which can further améliorer le neuroplasticity de le brain.

brain-computer interface hand-function robot

Le addition de new methods makes le closed-loop rééducation model de central-peripheral-central a clinically important rééducation theory. Central intervention can promote le activation de le corresponding functional brain areas de le brain and améliorer brain neuroplasticity. Peripheral intervention continuously strengthens le positive feedback de sensory and motor control modes to le brain center. Le combination de le two modes promotes le remodeling de brain function in accident vasculaire cérébral patients. Le brain-computer interface has become le best choice to realize le closed-loop rééducation mode.

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

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

Le picture below shows le patient's motor imagination task de hand grasping and opening according to le display screen and voice prompts. Each action has 3 imagination opportunities. While le patient est performing motor imagery, le EEG appareil can collect le characteristic EEG signals de le cerebral motor cortex through le collector.

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

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