Optimal electrode assembly automatic selecting method of brain-machine interface

A brain-computer interface and electrode group technology, applied in the input/output of user/computer interaction, computer components, mechanical mode conversion, etc., can solve the characteristics of incomplete electrode EEG signals, and restrict the practical application and promotion of BCI system , affect the classification accuracy of EEG signals, etc., to overcome the randomness, simplify the BCI system, and improve the system transmission rate.

Inactive Publication Date: 2012-07-04
BEIJING UNIV OF TECH
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AI Technical Summary

Problems solved by technology

However, the incompleteness of prior knowledge and the differences between people make this electrode not enough to be the best representative of the EEG signal characteristics in this area, which directly affects the classification accuracy of EEG signals and restricts the BCI system. Practical application and promotion

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  • Optimal electrode assembly automatic selecting method of brain-machine interface
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Embodiment Construction

[0049] The electrode cap and electroencephalogram instrument utilized in the present invention are commercially available, and are mainly used to collect electroencephalogram signals, and the electroencephalogram signals collected are converted into voltage amplitude forms through A / D and stored in a computer, which is convenient for post-processing and use.

[0050] Step 1: Follow the international 10-20 system standard to place electrodes, use the electroencephalogram to collect imaginary movement EEG signals from 118 electrode channels, and store them in the memory in the form of voltage amplitude.

[0051] Step 2: Design a 48-order, 512-sample FIR filter to perform 6-28Hz band-pass filtering on the EEG signal data in the memory, record the obtained EEG signal data set as S, classify each event, and classify Labels are denoted as {-1, 1}, -1 represents imagining right-hand movement, 1 represents imagining left-hand movement, and the classification label set is denoted as L....

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Abstract

The invention provides an optimal electrode assembly automatic selecting method of a brain-machine interface, which relates to the field of brain-machine interfaces. According to the invention, the automatic selection of the optimal electrode is realized; and the optimal electrode assembly automatic selection of an imagery motion brain-machine interface is realized by using a combined method of a common special pattern (CSP) and a support vector machine (SVM). The automatic selection of the optimal electrode assembly in the brain-machine interface has important effects on simplifying a brain-machine interface system and increasing system classification recognition rate and data transmission efficiency; and by using relevant property of an optimal support vector machine SVM linear kernel function as the optimal electrode screening index, redundant electrodes can be effectively deleted, the number of the electrodes can be obviously reduced, the useful electrodes can be kept, the system performance can be improved, and the precondition can be created to improve the popularization of a brain-machine interface technology.

Description

Technical field: [0001] The present invention relates to the field of brain-computer interface (brain-computer interface, BCI), realizes the automatic selection of the optimal electrode group, and specifically relates to the optimal electrode group for realizing the brain-computer interface of imaginary exercise by using the support vector machine (support vector machine, SVM) method Automatically selected. Background technique [0002] At present, there are many diseases that can damage the neural pathways that communicate and control the brain with the external environment, such as stroke, Parkinson's, motor neuron damage, etc., so that people lose part or all of their voluntary muscle control, and then lose part of their muscles. athletic ability. Today's rehabilitation technology can keep patients alive, but the quality of life of patients is low, which has caused a heavy burden to families and society. [0003] Brain-computer interface is a direct information exchange...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06F3/01A61B5/0478
Inventor 李明爱马建勇陆婵婵崔燕李骧杨金福阮晓钢
Owner BEIJING UNIV OF TECH
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