A method of upper limb rehabilitation training based on brain-computer interface and virtual reality technology

Abstract

The invention discloses an upper limb rehabilitation training method based on a brain-computer interface and a virtual reality technology. A patient wears an electrode cap and a pair of VR glasses, and a computer, an EEG amplifier and a smartphone are connected; the computer judges whether the patient is trained for the first time or not; if yes, EEG signals are collected, individualized classifier calibration is performed, and then one training is started; otherwise, one training is directly started; in the training process, the pair of VR glasses and the smartphone construct an upper limb training action scene for a first-person perspective for the patient, the patient controls motions of the upper limb in a virtual scene in real time through continuous exercise imagination practice, an BCI module in the computer automatically adjusts the classifier according to the current training effect of the patient; after training is finished, the classifier of the BCI module performs self-adaptation adjustment for next training, it is ensured that training difficulty adapts to the patient functional recovery situation, data collection does not need to be performed before each rehabilitation training for calibration, and time is shortened.

Description

technical field [0001] The invention relates to the technical field of limb rehabilitation for brain-injured patients, in particular to an upper limb rehabilitation training method based on brain-computer interface (brain-computer interface, BCI) and virtual reality (virtual reality, VR) technology. Background technique [0002] Studies have shown that early active rehabilitation training in patients with brain injury is beneficial to the recovery of their limb motor function, but patients with soft paralysis cannot promote the activity of related brain regions through active limb movement. Motor imagery and motor observation training based on the principle of mirror neurons in the brain provides an active rehabilitation training method that does not depend on peripheral muscle contraction for patients with brain injuries. The current clinical motor imagery training needs to guide patients to perform motor imagery through voice, and lacks effective monitoring and feedback me...

AI Technical Summary

Problems solved by technology

Its disadvantage is that after the rehabilitation training starts, patients do not need to continue to practice motor imagery, so the follow-up training reduces the requirement for the active participation of the patient, and actually becomes the patient's passive acceptance of training.

However, for patients with flaccid paralysis or spasticity who cannot control voluntary muscle contraction, the combination of robot-assisted limb movement and virtual reality scenes is still a passive rehabilitation training, and it is difficult to mobilize the patient's willingness to actively participate

Images