Audio-visual cognitive event-related electroencephalogram-based identification method

Abstract

The invention discloses an audio-visual cognitive event-related electroencephalogram-based identification method, which comprises the following steps of: performing wavelet packet decomposition and reconstruction on a series of filtered independent components to acquire electroencephalogram signals within electroencephalogram activity source rhythm ranges, and performing empirical mode decomposition on electroencephalogram signals of each rhythm to obtain corresponding feature mode components which reflect feature rhythm vibration modes; extracting inter-cognitive event phase locking strength features, inter-event synchronous features and driving and response coupling features from the feature mode components by adopting an inter-trial coherence index, a phase intrinsic coherence index, a phase shift intrinsic coherence index and a partial direct coherence index; extracting the power spectrum features of an audio-visual cognitive event-related electroencephalogram by adopting event-related spectral perturbation; and classifying the inter-cognitive event phase locking strength features, the inter-event synchronous features, the driving and response coupling features and the power spectrum features of cognitive events of a plurality of subjects by adopting a support vector machine multi-classifier to obtain identification results. According to the audio-visual cognitive event-related electroencephalogram-based identification method increases the identification rate.

Description

technical field [0001] The invention belongs to the field of identification, in particular to an identification method based on audio-visual cognitive event-related EEG. Background technique [0002] With the progress of society and the improvement of quality of life, the protection of information security will be related to the interests of individuals and the whole society. Today, identity recognition and authentication issues are involved in many fields. For example: In terms of information security, it is applied to information encoding and decoding and the safe delivery of resources. Due to the disadvantages of low reliability and easy loss, the traditional method of "identifying people by objects" can no longer meet the needs of the contemporary era. Instead, it uses the biological characteristics of people themselves, such as fingerprints and irises, for identification. However, each technology has limitations, and researchers are making unremitting efforts to explo...

AI Technical Summary

Problems solved by technology

[0006] However, there are still some shortcomings in the signal decomposition and feature extraction methods of cognitive EEG signals, which reduces the separability of EEG features caused by individual differences, and cannot better identify people.

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