Electroencephalogram signal detection method based on tensor method

A technology of EEG signals and detection methods, applied in diagnostic recording/measurement, medical science, psychological devices, etc., can solve the problems of destroying the original data structure and internal correlation of data, etc.

Active Publication Date: 2021-03-16
NORTH CHINA UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

[0004] The purpose of the present invention is to provide a method for detecting EEG signals based on the tensor method, so as to solve the

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  • Electroencephalogram signal detection method based on tensor method
  • Electroencephalogram signal detection method based on tensor method
  • Electroencephalogram signal detection method based on tensor method

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Embodiment Construction

[0017] The present invention will be described in detail below with reference to the various embodiments shown in the accompanying drawings, but it should be noted that these embodiments do not limit the present invention. Equivalent transformations or substitutions all fall within the protection scope of the present invention.

[0018] This embodiment provides an EEG signal detection method based on a tensor method, including the following steps:

[0019] Step 1, establish a PARAFAC model based on the collected EEG signals;

[0020] Step 2, using alternating least squares (alternating least squares, ALS) to perform psychological parameter feature extraction on the EEG signal to obtain a psychological parameter matrix, an EEG tester channel characteristic matrix and a collection environment matrix;

[0021] Step 3, carry out identifiability condition analysis on the psychological parameter characteristics through the uniqueness of the PARAFAC model;

[0022] Step 4: Perform ...

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Abstract

The invention discloses an electroencephalogram signal detection method based on a tensor method. The electroencephalogram signal detection method comprises the following steps: step 1, establishing aPARAFAC model based on collected electroencephalogram signals; step 2, performing psychological parameter feature extraction on the electroencephalogram signals by adopting an alternating least square method to obtain a psychological parameter matrix, an electroencephalogram tester channel feature matrix and an acquisition environment matrix; step 3, performing identifiability condition analysison the psychological parameter characteristics through the uniqueness of the PARAFAC model; and step 4, performing fast Fourier transform on the psychological generation mechanism of the electroencephalogram signal psychological parameter matrix, and the psychological abnormal factor parameter, so as to obtain an amplitude-frequency characteristic curve of the psychological parameter for later psychological diagnosis and treatment. The tensor of the invention has a research space in expression and analysis of high-dimensional data, and does not destroy internal structures of some data; and psychological characteristic parameters of the electroencephalogram signals are accurately detected and extracted.

Description

technical field [0001] The invention belongs to the technical field of EEG signal detection, in particular to an EEG signal detection method based on a tensor method. Background technique [0002] With the development of information science and technology, some wild ideas in people's brains are slowly turning into reality. Among them, EEG signals have been gradually applied in real life. EEG is the signal generated by the activity of neurons in the brain, which contains rich brain state information and a large amount of physiological information related to the human body. people's attention. Studies have shown that the EEG signals of different psychological changes are different, and when the psychology or emotion changes, the components of the EEG signals related to the psychology will also change. By reading the EEG signals, patients with mental disorders can be observed. Psychological changes. [0003] In the traditional method, the data is generally represented in the...

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Application Information

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IPC IPC(8): A61B5/16A61B5/372
CPCA61B5/165A61B5/7257
Inventor 韩曦刘芹姚敏郑争王瑞伟
Owner NORTH CHINA UNIVERSITY OF TECHNOLOGY
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