Emotion recognition method based on EEG and food picture data set

Abstract

The invention provides an emotion recognition method based on EEG and a food picture data set. The method comprises the steps of collecting food pictures, and screening out the food picture data set serving as a stimulating material; adopting single-channel EEG measuring equipment to collect EEG signals of a tested person; adopting a denoising method of stationary wavelet transform based on an artifact removal algorithm to preprocess the collected EEG signals; adopting wavelet packet transform to perform wavelet tree decomposition on the preprocessed EEG signals, and reconstructing a rhythm wave in each frequency band of the EEG signals corresponding to the last layer of nodes by reordering the last layer of nodes; extracting amplitude values and power spectrum characteristics of the EEG signal rhythm waves, and drawing an EEG signal spectrogram and a spectrum energy distribution diagram; and identifying the emotional state of the tested person based on statistical analysis of the amplitude values and the power spectrum characteristics of the EEG signals. According to the scheme, the problems of single selection of emotional stimulating materials and subjectivity of emotional measurement in the prior art are solved, and the accuracy of emotion recognition is improved.

Description

technical field [0001] The invention relates to the technical field of emotion recognition, in particular to an emotion recognition method based on EEG and food picture data sets. Background technique [0002] With the continuous development of technology, a new form of human-centered and human-driven digital media interaction (HCI) has the potential to revolutionize many areas of life, learning and entertainment. Driven by the emerging Internet media, people are surrounded by various visual food cues, not only in shopping malls, supermarkets or restaurants, but also on bulletin boards, advertisements, and TV programs. Psychological research has proved that people do have a process of emotional changes in this visual eating environment, and eating behaviors usually make eating decisions based on the relationship between visual food features and subsequent intake effects. Therefore, food pictures An effective substitute for real food. However, existing research in the field...

AI Technical Summary

Problems solved by technology

In addition, the existing food emotion database has little work on the collection of real-time EEG signal measurement data, and most of the experimental collection equipment is multi-electrode and multi-channel, and the wearing measurement of the testees in each experiment is very cumbersome and time-consuming

Therefore, it is challenging to extract effective emotional features from EEG signals by reducing the number of electrodes or simplifying the acquisition equipment.

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