Electroencephalogram emotion recognition method based on DEDBN-ELM

An emotion recognition and EEG technology, applied in the field of human-computer interaction, can solve the problems of further improvement of recognition rate, introduction of irrelevant features, feature omission, etc., and achieve the effect of automatic extraction, good robustness and high recognition rate

CN112508088APending Publication Date: 2021-03-16重庆邮智机器人研究院有限公司 +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2021-03-16

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Abstract

The invention relates to an electroencephalogram emotion recognition method based on DEDBN-ELM, and belongs to the field of human-computer interaction. The method comprises the steps that S1, decomposing electroencephalogram signals of all channels through EMD, and obtaining a series of IMF components; S2, selecting an IMF component according to the variance contribution rate; S3, constructing a DBN network for each electroencephalogram channel to extract the selected IMF components, and deep features of each channel are obtained respectively; and S4, taking the deep features of the pluralityof channels as the input of an extreme learning machine (ELM), and carrying out feature learning and classification. According to the method, it can be guaranteed that the recognition rate is high androbustness is good when feature extraction and classification are carried out on the positive emotion state, the negative emotion state and the neutral emotion state in the electroencephalogram dataset.
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Description

technical field

[0001] The invention belongs to the field of human-computer interaction, and relates to an EEG emotion recognition method based on DEDBN-ELM. Background technique

[0002] At present, emotion recognition mainly focuses on two aspects of human non-physiological signals and physiological signals. Emotion recognition based on physiological signals can avoid the camouflage and subjectivity of emotions, so it can better evaluate people's emotional state. In emotion recognition based on physiological signals, since the electroencephalogram (EEG) signal is directly extracted from the brain and can better reflect the activity state of the brain, it has attracted much attention and has become the focus of research in the field of emotion recognition. At present, wavelet transform, wavelet packet transform and empirical mode decomposition (EMD) methods have been proposed. EMD can perform adaptive decomposition according to the characteristics of the signal itself, an...

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Embodiment Construction

[0047] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic concept of the present invention, and the following embodiments and the features in the embodiments can be combined with each other in the case of no conflict.

[0048] Wherein, the accompanying drawings are for illustrative purposes only, and represent only schematic diagrams, rather than physical drawings, and should...