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Multichannel electroencephalogram signal channel selection method based on time-frequency co-melting

An EEG signal and channel selection technology, which is applied in medical science, sensors, diagnostic recording/measurement, etc., can solve problems such as the inability to flexibly select the brain-computer interface channel and the inability of a single channel to provide sufficient information.

Active Publication Date: 2021-03-19
SHANGHAI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003]The purpose of the present invention is to overcome the problems existing in the prior art that the brain-computer interface channel cannot be flexibly selected, and to provide a multi-channel brain-computer interface based on time-frequency integration. Electrical signal channel selection method
This method solves the difficulty that a single channel cannot provide enough information, and at the same time avoids the interference information contained in the acquisition and task-independent channels from affecting the results

Method used

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  • Multichannel electroencephalogram signal channel selection method based on time-frequency co-melting
  • Multichannel electroencephalogram signal channel selection method based on time-frequency co-melting
  • Multichannel electroencephalogram signal channel selection method based on time-frequency co-melting

Examples

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Embodiment 1

[0072] In this example, refer to figure 1 , a multi-channel EEG signal channel selection method based on time-frequency fusion, the operation steps are as follows:

[0073] a. EEG signal preprocessing:

[0074] Reduce the sampling frequency, use wavelet transform to correct baseline drift, band-pass filter, and independent component analysis to remove oculograph signal interference;

[0075] b. Use the time-frequency fusion method to obtain correlation information between channels;

[0076] c. Feature extraction using co-space patterns;

[0077] d. Use the support vector machine to train the classification model, input the test set into the classification model, and obtain the classification accuracy data;

[0078] e. Perform result analysis, and obtain classification accuracy results of various channel selection methods according to the result information.

[0079] The method of this embodiment solves the difficulty that a single channel cannot provide enough information,...

Embodiment 2

[0081] This embodiment is basically the same as Embodiment 1, especially in that:

[0082] In this example, see figure 1 , a multi-channel EEG signal channel selection method based on time-frequency fusion, the operation steps are as follows:

[0083] a. EEG signal preprocessing:

[0084] Preprocess the collected EEG data; resample and down-frequency all the collected EEG data as needed; then perform baseline drift correction, and select the filter passband for filtering according to the research content; use independent component analysis to convert the EEG Signal removal to prevent it from interfering with experimental results;

[0085] b. Time-frequency fusion method to obtain correlation information

[0086] Integrate the time and frequency components of the EEG signal; use the time-frequency analysis method based on wavelet transform; perform wavelet transform on the preprocessed data to obtain the time-frequency power information of each channel and each frequency, an...

Embodiment 3

[0134] This embodiment is basically the same as the above-mentioned embodiment, and the special features are:

[0135] In this example, see figure 1 , a channel selection method for multi-channel EEG signals based on the time-frequency fusion method, the operation steps are as follows:

[0136] a. EEG signal preprocessing

[0137] According to the content of the above-mentioned invention content a, the collected motor imagery EEG data is preprocessed; the collected EEG data is resampled and down-converted to 250Hz; the baseline drift is corrected by wavelet transform, and a Butterworth-based The second-order IIR filter performs band-pass filtering with a passband of 8-30 Hz; performs 8-30 Hz band-pass filtering to retain the motor imagery signal characteristics contained in the α wave and β wave frequency bands, and remove most of the myoelectric noise interference; Oculoelectric signals also exist in the 8-30Hz frequency band as noise, so independent component analysis is u...

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Abstract

The invention discloses a multichannel electroencephalogram signal channel selection method based on time-frequency co-melting, and belongs to the field of brain-computer interface data processing. The method comprises the following operation steps: 1) performing data preprocessing, namely reducing sampling frequency, and performing baseline drift correction, band-pass filtering and independent component analysis by using wavelet transform to remove electrooculogram signal interference; 2) acquiring inter-channel correlation information by a time-frequency co-melting method; 3) performing feature extraction by using a common spatial pattern (CSP) 4) performing feature classification by using a support vector machine; and 5) performing result analysis. The method has remarkable innovativeness and feasibility, and has important reference significance for real-time processing and optimization of electroencephalogram signals.

Description

technical field [0001] The invention relates to a multi-channel EEG signal channel selection method based on time-frequency fusion, which is applied in the field of brain-computer interface data processing. Background technique [0002] The brain-computer interface system is a research hotspot in recent years, which can connect and communicate the brain thinking with computers or other external devices. At this stage, BCI technology is mainly used to help people with normal brain thinking but unable to move independently and freely complete some daily activities. Motor imagery means that a person directly imagines a certain body movement through the brain without any physical movement. Motor imagery produces EEG signals. When people only imagine a certain movement but do not execute it, the same EEG signal as that of performing the movement will be generated in the motor sensory area of ​​the brain. By analyzing such signals, the intention of the imaginer can be judged. A...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/372A61B5/374
CPCA61B5/7203A61B5/7225A61B5/7264A61B5/726Y02D30/70
Inventor 任彬潘韫杰
Owner SHANGHAI UNIV
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