Brain electrical nerve feedback training system and method for improving motor learning function

Abstract

The invention relates to a brain electrical nerve feedback training system and method for improving a motor learning function. The system comprises a brain electrical signal collecting module, a brain electrical signal analysis module, a nerve feedback module, an auxiliary equipment module and a feedback output module, all of which are connected in a wireless mode or a wired mode, and the brain electrical signal collecting module is connected with the brain electrical signal analysis module. The brain electrical signal collecting module collects brain electrical signals and transmits the brain electrical signals to the brain electrical signal analysis module. The brain electrical signal analysis module carries out feature extraction and classification on the brain electrical signals and transmits the brain electrical signals to the nerve feedback module. The nerve feedback module is connected with the brain electrical signal analysis module, the feedback output module and the auxiliary equipment module to achieve optimizing and adjusting functions of brain electrical nerve feedback training. According to the brain electrical nerve feedback training system and method, targeted training can be carried out according to the motor learning nerve feedback scene, the preparation time in the nerve feedback training process is shortened, the specialty requirement in the nerve feedback training process is reduced, the application scene of the nerve feedback training is expanded, and the improving effect of the nerve feedback training on the motor learning capacity is improved.

Description

technical field [0001] The invention belongs to the technical field of medical devices, in particular to an EEG neurofeedback training system and method for improving motor learning functions. Background technique [0002] Neurofeedback is a technology produced by the intersection of neuroscience and biomedical engineering. Its principle is to collect the physiological activities of the subjects and feed them back to the subjects in a certain form online in real time, so that the subjects Able to actively regulate the state of bodily functions. Neurofeedback in the narrow sense is mainly based on EEG signals, while neurofeedback in the broad sense can use a variety of different physiological signals including EEG signals, such as ECG, EMG, and respiratory rhythm. [0003] The neurofeedback technology based on EEG signals is widely used. It mainly collects the EEG signals of the subjects, and after computer processing and analysis, the EEG characteristics of the subjects are...

AI Technical Summary

Problems solved by technology

At present, there are the following technical problems based on neurofeedback technology: (1) EEG signals are weak and complex, how to select appropriate features so that they can effectively reflect the state of the brain related to motor learning, and be able to provide information for the subjects. Provide effective guidance; (2) How to select an appropriate form of feedback to enable the subjects to understand and accurately grasp the EEG state; (3) How to formulate and efficiently feedback the working mode or process of the training system to enable Subjects complete neurofeedback training in a relatively short period of time, avoiding fatigue

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