A Brain-Computer Interface Method Based on Gray Theory

A technology of brain-computer interface and gray theory, applied in the field of brain-computer interface research, can solve problems such as weak signal amplitude and strong background noise

Active Publication Date: 2021-09-10
NORTHWESTERN POLYTECHNICAL UNIV
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  • Claims
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AI Technical Summary

Problems solved by technology

[0003] Studies have shown that EEG signals have the characteristics of strong background noise, weak signal amplitude, strong non-stationarity and randomness, and prominent frequency domain features. Therefore, the analysis and processing of EEG signals is still a very challenging topic.

Method used

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  • A Brain-Computer Interface Method Based on Gray Theory
  • A Brain-Computer Interface Method Based on Gray Theory
  • A Brain-Computer Interface Method Based on Gray Theory

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Experimental program
Comparison scheme
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Embodiment Construction

[0035] specific implementation plan

[0036] 1. Alpha wave pattern recognition based on improved gray modeling method

[0037] Processing flow such as figure 1 shown.

[0038] 1.1 First, filter the original EEG data at 4-30Hz, and set the original data length to 0.5s and 100 points.

[0039] 1.2 The filtered numerical sequence is upgraded as the original sequence of the gray model GM (1,1), that is, the non-negative sequence X (0) (k)=[X (0) (k)|k=1,2,…,n], find the accumulation sequence X (1) (k)=[X (1) (k)|k=1,2,...,n]. Here G stands for gray, M stands for model, the first 1 in brackets stands for a first-order equation, and the second 1 stands for a variable.

[0040]1.3 Introduce the smoothing coefficient u to improve the gray model, according to the cumulative sequence X (1) (k) Establish an improved GM (1, 1), build a model for every 10 points, the model is as follows:

[0041]

[0042] in, a is the development coefficient, and b is the gray action.

[004...

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Abstract

The present invention proposes a brain-computer interface method based on gray theory, which relates to the field of brain-computer interface research, and specifically relates to a brain-computer interface brain electrical signal processing method. The method includes: the method includes: 1. Improving the GM(1,1) model by introducing a smoothing coefficient u; thereby improving the discrimination ability of the model parameters; 2. Extracting good signals through the statistical characteristics of the model parameters 3. A brain-computer interface method based on gray theory is proposed, and an improved gray modeling method is used to realize state switching, and a method based on gray association is used to realize instruction recognition. The actual measurement shows that the present invention can effectively realize the state transition and instruction recognition in the brain-computer interface.

Description

technical field [0001] The invention relates to the field of brain-computer interface research, in particular to an EEG signal processing method of the brain-computer interface, in particular to a brain-computer interface method based on gray theory. Background technique [0002] Brain-computer interface (Brian-Computer-Interface, BCI) is a new human-computer interface method based on EEG signals to realize the communication and control between human brain and computer or other electronic equipment. It establishes a direct communication and control channel between the human brain and computers or other electronic devices by collecting and analyzing the bioelectrical signals of the human brain, so as to express wishes or manipulate devices through the human brain without language and body movements. A brain-computer interface system usually includes three modules: signal acquisition, signal processing and device driver, among which signal processing is the core part of the br...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F3/01G06K9/00
CPCG06F3/015G06F2218/02G06F2218/08G06F2218/12
Inventor 刘畅谢松云吴悠段绪谢辛舟
Owner NORTHWESTERN POLYTECHNICAL UNIV
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