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EMD and CSP fusion power spectral density electroencephalogram feature extraction method

A power spectral density and feature extraction technology, which is applied in the field of EMD and CSP fusion power spectral density EEG feature extraction, can solve problems such as multi-input and lack of frequency domain

Inactive Publication Date: 2018-11-27
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

Step 3, calculate the power spectral density value of the signal matrix to optimize the signal, and then decompose the public space mode to solve the problem of CSP multi-input and lack of frequency domain information

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  • EMD and CSP fusion power spectral density electroencephalogram feature extraction method
  • EMD and CSP fusion power spectral density electroencephalogram feature extraction method
  • EMD and CSP fusion power spectral density electroencephalogram feature extraction method

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Embodiment Construction

[0074] Specific embodiments of the present invention are described in detail below, but it should be understood that the protection scope of the present invention is not limited by the specific embodiments.

[0075] Unless expressly stated otherwise, throughout the specification and claims, the term "comprise" or variations thereof such as "includes" or "includes" and the like will be understood to include the stated elements or constituents, and not Other elements or other components are not excluded.

[0076] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0077] Such as figure 1 Shown, method of the present invention comprises the steps:

[0078] Step 1: Select the EEG signals of 9 subjects as the training set and test set, and preprocess the signals in the two channels of C3 and C4 of a single subject respectively;

[0079] Step 2: Perform empirical mode decomposition on the preprocessed EEG signal x(t); o...

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Abstract

The invention discloses an EEG and CSP fusion power spectral density electroencephalogram feature extraction method. Firstly, the acquired electroencephalogram is preprocessed, and the denoised signals are subjected to empirical mode decomposition to obtain a plurality of intrinsic mode functions. The correlation coefficient between the original electroencephalogram experiment and each order IMF component at each experiment is calculated, and the average value of the absolute values of the correlation coefficients obtained from all experiments is calculated, the intrinsic mode function with alarger correlation coefficient absolute value average value is selected, the power spectral density is calculated and is used as a feature, the corresponding feature vectors are extracted through theco-spatial mode projection mapping and classified by using a support vector machine. The imagine action average classification accuracy of 9 subjects is over 96%, and the feasibility and effectivenessof the method are guaranteed.

Description

Technical field: [0001] The invention relates to an EMD and CSP fusion power spectral density EEG feature extraction method, belonging to the technical field of intelligent information processing. Background technique: [0002] Brain Computer Interface (BCI) is a control technology involving many disciplines and knowledge fields. In the 1990s, the concept of brain-computer interface was proposed: it is a channel for direct transmission of information established between the human or animal brain and external equipment, and recognizes human thoughts by collecting and extracting EEG signals generated by the brain. . The development of brain-computer interface technology can help patients with movement disorders improve their self-care ability and quality of life, and can enhance their communication and interaction with the external environment by controlling external auxiliary devices such as computers, speech synthesizers, auxiliary applications, and neuroprosthetics through...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0476
CPCA61B5/7225A61B5/7264A61B5/369
Inventor 张学军陈启超何涛成谢锋
Owner NANJING UNIV OF POSTS & TELECOMM
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