A kind of electroencephalogram signal classification method, device, equipment and medium

Abstract

The present application provides a method for classifying EEG signals, the method comprising: obtaining an EEG signal sequence to be identified; inputting the EEG signal sequence to be identified into an EEG signal classification model to obtain the EEG signal sequence to be identified EEG classification information, the EEG classification information includes motor imagery EEG signals and steady-state visual evoked potential EEG signals.

Description

technical field [0001] The present application relates to the technical field of data processing, in particular, to a method, device, device and medium for classifying electroencephalogram signals. Background technique [0002] Brain-computer interface (BCI) technology is a direct connection path established between human brain or animal brain (or brain cell culture) and external equipment. Brain-computer interface is a multidisciplinary research field, the core disciplines involve cognitive science, neural engineering, automatic control, etc. Specifically, the brain-computer interface technology is divided into three steps: (1) EEG acquisition, collecting the user’s EEG signals through the EEG acquisition equipment, using a computer to analyze the EEG signals, and classifying the EEG signals; (2) ) Instruction conversion, converting the classified EEG signals into machine control instructions through the computer; (3) Instruction transmission, sending the converted instruc...

AI Technical Summary

Problems solved by technology

[0004] In view of this, the purpose of this application is to provide an EEG signal classification method, device, equipment and medium for solving the problem of poor classification accuracy of EEG signals in the prior art

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