Emotion-recognition-oriented electroencephalogram signal channel selection method, system and application

Abstract

The invention belongs to the technical field of machine learning and intelligent human-computer interaction, and discloses an emotion-recognition-oriented electroencephalogram signal channel selectionmethod, system and application. The method comprises the following steps: performing debasing preprocessing on EEG data; calculating the power spectrum intensity of a frequency domain signal by combining a sliding window and fast Fourier transform, and taking the power spectrum intensity as electroencephalogram characteristics; respectively solving the weight of each feature by adopting ReliefF and MIC algorithms, performing integrating by utilizing a wave arrival counting method to obtain an integral sum of each channel, sequentially adding feature data of a channel with a relatively large integral sum value, performing classifying by adopting a random forest, and finding out an optimal channel subset; and performing classification evaluation. According to the method, a feature selectionmethod combining ReliefF and MIC algorithms is adopted, each channel serves as a whole, the purpose of greatly reducing the number of the channels is achieved, the efficiency of the system can be improved, the real-time performance of the system can be improved, and the method has important significance in the fields of electroencephalogram emotion recognition and intelligent man-machine interaction.

Description

technical field [0001] The invention belongs to the technical field of machine learning and intelligent human-computer interaction, and in particular relates to an emotion recognition-oriented EEG signal channel selection method, system and application. Background technique [0002] In recent years, emotion recognition has become a hot topic in the fields of affective computing, computational neuroscience, and human-computer interaction. At the same time, it has been widely used in many fields such as medical care, education, games, and aviation. At present, many scholars choose EEG signals to carry out related research on emotion recognition for the following reasons. First of all, EEG signals are physiological signals, and physiological signals are directly controlled by the nervous system and endocrine system, which are spontaneous and not affected by human subjective consciousness; secondly, EEG signals are directly generated by the central nervous system closely related...

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Problems solved by technology

In addition, there are individual differences among the subjects, so the channel selection results obtained for different subjects may be different

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