An EEG Feature Extraction Method Based on Dominant Electrode Combination and Empirical Mode Decomposition

Abstract

An electroencephalogram (EEG) feature extraction method based on dominant electrode combination and empirical mode decomposition (EMD) includes inputting n-channel EEG signal data, selecting dominant electrodes according to the principle that electrodes with record of EGG signals having classification performance higher than a certain threshold are called the dominant electrodes, otherwise, are called non-dominant electrodes, selecting dominant combinations, respectively extracting feature of EGG data of a training sample set and EGG data of a testing sample set corresponding to each dominant combination by means of the EMD to acquire training feature vector and testing feature vector of each dominant combination, respectively inputting the training feature vector, the testing feature vector, training sample set label, testing sample set label of each dominant combination input a naive Bayesian classifier to classify to obtain classification accuracy of each dominant combination, and finally surmising relation between different stimulations and activated brain regions when executing relevant motor imagery tasks according to the classification accuracy of each dominant combination.

Description

technical field [0001] The invention relates to the field of pattern recognition, in particular to a method for extracting features of electroencephalogram signals. Background technique [0002] The recognition of EEG signals is a multi-disciplinary research subject such as cognitive neuroscience, signal processing and computer science. How to reasonably apply this knowledge to extract effective information from EEG signals that can represent different states of the human body has always been an important issue for EEG signals. Hotspots and difficulties in the field of research. [0003] Psychological research has found that different stimuli or experimental tasks can cause neurons with different structures in the brain to produce discharge behavior. Therefore, in the research process of EEG signals, the screening of electrodes is an indispensable link. Traditional EEG processing methods are based on psychological conclusions. However, psychological conclusions are usually...

AI Technical Summary

Problems solved by technology

[0006] To sum up, the existing technology has the following problems: (1) It is impossible to precisely locate the electrode position directly related to the task or stimulus; (2) The information is redundant; (3) It is impossible to infer the stimulus when performing the motor imagery task. Activation of connections between brain regions

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