Electrode optimization method based on brain source imaging technology

A technology of electrodes and brain sources, applied in the direction of electrical digital data processing, pattern recognition in signals, input/output process of data processing, etc., can solve the problem of increasing acquisition and signal processing costs, limiting the application of portable BCI systems, and unpredictable Issues such as unknown electrode contribution

Active Publication Date: 2018-10-19
BEIJING UNIV OF TECH
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Problems solved by technology

[0008] However, these methods have certain limitations: they can only calculate the contribution of known electrodes, and cannot predict the contribution of unknown

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  • Electrode optimization method based on brain source imaging technology
  • Electrode optimization method based on brain source imaging technology
  • Electrode optimization method based on brain source imaging technology

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Embodiment Construction

[0043] The specific embodiment of the present invention will be further described in conjunction with the accompanying drawings. figure 2 A general flow diagram of electrode optimization is shown. This implementation is carried out in the simulation environment of matlab, taking imagining the right hand and right foot as an example, using known 25-lead electrodes (refer to image 3 ) to predict the F-score of 63-lead electrodes (see Figure 4 ).

[0044] Such as Figure 8 As shown, the present invention provides a method for optimizing electrodes based on brain-derived imaging technology, comprising the following steps:

[0045] 1. According to the international standard lead 10-20 system, select 25 lead electrodes evenly distributed in the cerebral cortex. A 48-order FIR filter with 512 sampling points is designed to filter the EEG data with an 8-30HZ band-pass filter to achieve the purpose of removing interference noise.

[0046] 2. Use the improved Fisher criterion to...

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Abstract

The invention discloses an electrode optimization method based on a brain source imaging technology. An improved Fisher criterion is used for solving the F score of each collected electrode which is evenly distributed; a brain source imaging technology is used for carrying out inverse transformation on the obtained F score to the cortex to obtain corresponding brain source distribution; an electroencephalogram forward problem is solved, i.e., on a premise that a transfer matrix between the cortex and dandruff is known, and the estimation value of the F score of an unknown electrode is solved;and finally, the estimation value of the F score is subjected to descending sorting, and parts of electrodes with a highest score value are selected as an optimal electrode. By use of the method, theproblems that electrode optimization depends on experiences or an amount of experiment collection electrodes in a motor imagery task is large can be solved, and the functions that a small quantity ofelectrodes is used for pre-estimating the contribution degree of the unknown electrode and the electrode optimization is carried out can be realized.

Description

technical field [0001] The invention belongs to the technical field of electroencephalogram (EEG) processing, in particular to a method for optimizing motor imagery EEG electrodes in a Brain-Computer Interface (BCI) system, using improved Fisher criteria and EEG Source imaging (EEG Source Imaging, ESI) combined method for optimal electrode selection. Background technique [0002] The aging population, stroke, hemiplegia and traffic accidents have caused a large number of patients with spinal lesions or injuries. The action commands issued by their brains cannot pass through the normal output channel of motor nerve action signals, thus losing part of their limb movement ability. Traditional rehabilitation medicine methods can provide rehabilitation treatment for some patients. However, this artificial rehabilitation treatment method is expensive and brings a heavy burden to family members and society. [0003] BCI has brought good news to rehabilitation patients. It is a sy...

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Application Information

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IPC IPC(8): G06F3/01G06K9/00
CPCG06F3/015G06F2203/012G06F2218/02
Inventor 李明爱张春亭王一帆孙炎珺
Owner BEIJING UNIV OF TECH
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