Identity recognition method based on electroencephalogram signal channel attention convolutional neural network

A technology of convolutional neural network and EEG signal, which is applied in the identification field of biometric feature extraction algorithm, can solve problems such as potential safety hazards, and achieve the effects of easy acquisition, enhanced feature propagation, and shortened number of neurons

Pending Publication Date: 2021-08-13
CHENGDU UNIV OF INFORMATION TECH
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Problems solved by technology

Therefore, there are certain hidden dangers in the traditional identification method.

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  • Identity recognition method based on electroencephalogram signal channel attention convolutional neural network
  • Identity recognition method based on electroencephalogram signal channel attention convolutional neural network
  • Identity recognition method based on electroencephalogram signal channel attention convolutional neural network

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[0030] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings.

[0031] Such as figure 1 As shown, a kind of identification method based on EEG signal channel attention convolutional neural network of the present invention comprises the following steps:

[0032] S1, select data, select EEG signals of different channels from the emotional EEG database as the original signal;

[0033] The database of EEG signals comes from the publicly available HeadIT Emotion EEG dataset, which contains both positive and negative emotion tasks. In this embodiment, a total of 20 healthy volunteers participated in the experiment. Stimulate subjects through guided language narratives to induce a realistic emotion; there are 15 guided image narratives in total, each describing different emotions and situations, separated by voice-guided relaxation episodes; subjects use The image, as the embodiment of the emotion that inspire...

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Abstract

The invention discloses an identity recognition method based on an electroencephalogram signal channel attention convolutional neural network. The method comprises the following steps that S1, EEG signals of different channels are selected from an emotion electroencephalogram database to serve as original signals; S2, a band-pass filter is used for removing electro-oculogram artifact signals and power frequency interference signals in the original signals to obtain pure emotion electroencephalogram signals; and S3, the preprocessed emotion electroencephalogram signals are input into a deep learning identity recognition model, and a deep learning algorithm is used for carrying out identity recognition on the emotion electroencephalogram signals. According to the method, the emotion EEG signals are selected for identity recognition, the emotion EEG is easy to obtain, and the identity recognition method has higher universality and generalization. According to the method, the number of neurons connected between the front layer and the rear layer is reduced, the gradient disappearance problem is solved, feature propagation is enhanced, network parameters are reduced, EEG signal features in different emotion states are more effectively utilized, and therefore identity recognition of the emotion electroencephalogram signals is effectively carried out.

Description

technical field [0001] The invention relates to the technical fields of communication electronics technology and biometric feature identification, in particular to an identification method based on a biometric feature extraction algorithm of emotional EEG signals. Background technique [0002] In recent years, the Internet and smart cities have brought opportunities for economic development, but also brought many security risks, some of which are related to the identification and verification of identity information. Traditional identification methods such as face recognition, iris recognition, fingerprint recognition, etc., all have the disadvantages of being easily tampered with, copied, and used under duress, thus posing certain security risks. With the development of technology and the continuous intelligence and technology of criminal means, biometric identification technology faces new challenges. Traditional biometric identification methods are mainly face recognitio...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/372A61B5/117
CPCA61B5/117A61B5/7264A61B5/7267A61B5/7235
Inventor 郜东瑞张云霞李鑫王宏宇郑文银王珂杰严明靖汪漫青张欢张永清
Owner CHENGDU UNIV OF INFORMATION TECH
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