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Peripheral nerve electrical stimulation based MI-BCI training method

A training method and peripheral nerve technology, applied in electrotherapy, treatment, medical science, etc., can solve the problems of poor classification accuracy of MI-BCI, achieve the effect of improving imagination, removing clutter, and improving classification accuracy

Active Publication Date: 2018-12-25
BEIJING MECHANICAL EQUIP INST
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of the above analysis, the embodiment of the present invention aims to provide a MI-BCI training method based on peripheral nerve electrical stimulation to solve the problem of poor MI-BCI classification accuracy in the prior art

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  • Peripheral nerve electrical stimulation based MI-BCI training method

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Embodiment 1

[0061] A specific embodiment of the present invention discloses a MI-BCI training method based on peripheral nerve electrical stimulation, such as figure 1 As shown, the MI-BCI training method based on peripheral nerve electrical stimulation comprises the steps:

[0062] S1. Sequentially number the K subjects, and select l specified actions that each subject can perform with the left or right hand. The specified actions should be as simple and typical as possible, suitable for experimental research.

[0063] S2. Perform electrical stimulation on the peripheral nerves of the designated parts of the subject's body. After the stimulation is over, perform the post-stimulation MI-BCI task (MI task), imagine that the left or right hand performs each of the above-mentioned specified actions, and collect each An EEG signal corresponding to the specified action. Specifically, the EEG signal of the cerebral cortex of the subject is collected by the EEG collection system, and theoretic...

Embodiment 2

[0069] Optimizing on the basis of Example 1, such as figure 2 As shown, the MI-BCI training method based on peripheral nerve electrical stimulation can include the following steps:

[0070] S1. Sequentially number the K subjects, and select l specified actions that each subject can perform with the left or right hand. The specified actions include fist-making actions of the left hand and the right hand. In this experiment, a total of 14 subjects participated in the EEG data collection.

[0071] S2. Before implementing electrical stimulation, perform the pre-stimulation MI-BCI task, imagine that the left hand or right hand performs each of the specified actions, and at the same time collect the EEG signals corresponding to each of the specified actions. Preferably, the acquisition system for collecting EEG signals is a Neuroscan 64-lead EEG acquisition system, and the electrodes are Ag / AgCl electrodes, with the subject's forehead as the ground and the tip of the nose as the ...

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Abstract

The invention relates to a peripheral nerve electrical stimulation based MI-BCI training method, and belongs to the technical field of brain-computer interfaces, which solves the problem of poor accuracy of MI-BCI classification in the prior art. The peripheral nerve electrical stimulation based MI-BCI training method disclosed in the invention is a novel MI-BCI training method, which improves theactivity of a corresponding functional area of a cerebral cortex by performing electrical stimulation on the human peripheral nerve at a specific frequency, can improve the cerebral cortex's imagination ability to use the relevant functional areas, can quickly improve the accuracy of the MI-BCI classification, and contributes to the practical application of the MI-BCI.

Description

technical field [0001] The invention relates to the technical field of brain-computer interface, in particular to an MI-BCI training method based on electrical stimulation of peripheral nerves. Background technique [0002] Brain-Computer Interface (BCI) can monitor or identify signals representing human brain thinking and ideas through computers, convert them into computer instructions, and directly complete external control and communication. Motor imagery (MI), with motor intentions but no actual motor output, can cause an increase or decrease in the amplitude of mu and beta rhythms in the sensory motor cortex (ERD or ERS). [0003] The MI-BCI system (MI-BCI) is the only BCI paradigm that directly reflects the user's subjective movement awareness without external stimuli. It judges the user's movement by identifying specific EEG changes induced by different tasks. intention. The MI-BCI mode is in line with the state of normal thinking activities of the brain, and can "t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61N1/36A61B5/0476
CPCA61N1/36014A61B5/369
Inventor 奕伟波范新安陈远方张利剑明东
Owner BEIJING MECHANICAL EQUIP INST
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