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Electroencephalogram signal recognition method

A technology of EEG signal and recognition method, which is applied in the field of EEG signal, can solve the problems of low robustness of signal recognition and low recognition rate of EEG P300 signal, and achieve the effect of solving low robustness

Pending Publication Date: 2021-04-06
GUANGDONG OCEAN UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The purpose of the present invention is to provide an EEG signal recognition method for the above existing problems, which solves the problem of low recognition rate of EEG P300 signals, and solves the problem of low robustness of signal recognition

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  • Electroencephalogram signal recognition method
  • Electroencephalogram signal recognition method
  • Electroencephalogram signal recognition method

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Embodiment 1

[0039] The invention discloses an embodiment of an EEG signal recognition method. Firstly, the EEG signal is collected. The experimental data in this paper are provided by the P300 brain-computer interface of five healthy adult subjects (S1-S5). Each subject can observe a character matrix composed of 36 characters, and the character matrix is ​​in units of rows or columns (a total of 6 rows and 6 columns), such as figure 1 shown. The acquisition equipment collects EEG data from the subjects at a sampling rate of 250Hz. The data is divided into two categories, including training set and test set.

[0040] The specific data collection process is: after entering the flashing mode of the character matrix, each time a row or a column of the character matrix is ​​flashed in random order, the flashing time is 80 milliseconds, and the interval is 80 milliseconds; finally, when all the rows and columns are flashing once After that, a round of experiments ends. When the subjects star...

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Abstract

The invention discloses an electroencephalogram signal recognition method, and the method comprises the following steps: collecting electroencephalogram signals, and dividing the collected data into two types, including a training set and a test set; collecting the electroencephalogram signals through a P300 brain-computer interface, and when the electroencephalogram signals are collected, measuring the electroencephalogram signals, generated when a person sees corresponding characters, as a data source; preprocessing the electroencephalogram signals; acquiring a priority signal channel; constructing a generative adversarial network, and analyzing and identifying the electroencephalogram signal through the generated adversarial network. By the adoption of the method, the problem that the electroencephalogram P300 signal recognition rate is low is solved, and the problem that the signal recognition robustness is low is solved.

Description

technical field [0001] The invention relates to the technical field of electroencephalogram signals, in particular to a method for identifying electroencephalogram signals. Background technique [0002] The brain is the center of high-level neural activity in the human body, with hundreds of millions of neurons, which transmit and process human information through interconnection. EEG signals can be divided into evoked EEG signals and spontaneous EEG signals according to the way they are generated. P300 event-related potential is a kind of evoked EEG signal. As an endogenous component, it is not affected by the physical characteristics of the stimulus. It is related to perception or cognitive psychological activities, and is closely related to processing processes such as attention, memory, and intelligence. The EEG signals collected during sleep are spontaneous EEG signals. Spontaneous sleep EEG signals can reflect changes in the body's own state, and are also an importan...

Claims

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Application Information

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IPC IPC(8): A61B5/378A61B5/00
CPCA61B5/7267A61B5/7225A61B5/7203
Inventor 李升陈家锐陈宝琴杨培浩陈炳材张军
Owner GUANGDONG OCEAN UNIVERSITY