Brain electric features based emotional state recognition method

A state recognition and emotion technology, applied in the field of emotional state recognition based on EEG features, which can solve the problems of effectively extracting EEG features and affecting the recognition rate.

Active Publication Date: 2012-10-10
TIANJIN UNIV
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AI Technical Summary

Problems solved by technology

The presence of background signals interferes with the effective extraction of emotion-related EEG features, affecting the recognition rate to a certain extent

Method used

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  • Brain electric features based emotional state recognition method
  • Brain electric features based emotional state recognition method
  • Brain electric features based emotional state recognition method

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Embodiment Construction

[0058] The EEG feature-based emotional state recognition method of the present invention will be described in detail below in conjunction with the embodiments and the accompanying drawings.

[0059] The emotional state recognition method based on EEG features proposed by the present invention applies co-space mode filtering to the evoked EEG of multiple types of emotional pictures to enhance the EEG components related to emotional tasks, and then extracts features for classification and recognition, and the ideal result is obtained. recognition rate.

[0060] Such as figure 1 As shown, the emotional state recognition method based on EEG features of the present invention includes the following stages:

[0061] (1) In the data collection stage, the data collection is to extract the 64-lead EEG data of the subjects induced by pictures of different levels of pleasure under the conditions of international emotion pictures;

[0062] (2) Data preprocessing stage,

[0063] The collec...

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Abstract

The invention discloses a brain electric features based emotional state recognition method. The method comprises the following steps of: data acquisition stage: under the condition of international emotional picture induction, extracting 64 brain electric data which is tested under the induction of different-happiness-level pictures; data pretreatment stage: carrying out four stages of reference electric potential variation, down sampling, band-pass filtering, electro-oculogram removal on the collected 64 brain electric data; feature extraction stage: extracting time domain features after signals after pretreatment are filtered by a common space model algorithm; and feature recognition: recognizing the features by using a support vector machine classifier, and differentiating different emotional states. According to the method, an OVR (one versus rest) common space model algorithm is used for removing the interference of background signals, and is used for the signal intensification of multiple types of emotion induced brain electricity; after the background signals are removed, the differences among different types of emotional brain electricity are intensified, the recognition accurate ratio of subjects is relatively ideal when the recognition is carried out by the time domain variance features, and the emotions of different happiness can be differentiated accurately.

Description

technical field [0001] The invention relates to a method for identifying an emotional state. In particular, it relates to an emotional state recognition method based on EEG characteristics that can be used for the diagnosis and curative effect evaluation of clinical emotional disorders and neurofeedback regulation of emotions. Background technique [0002] Emotion is a high-level function of the human brain, which ensures the survival and adaptation of organisms, and has an important impact on individual learning, memory, and decision-making. Emotions are also a source of individual variation and are a key component of many personality traits and psychopathologies. With the development of society, people of all ages and fields are experiencing more and more emotional distress, and the incidence of various emotional-related diseases is increasing, such as depression, mania, anxiety, obsessive-compulsive symptoms, emotional disorders, etc. The correct identification and reg...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/16A61B5/0476
Inventor 张迪明东陈龙李南南柯余峰许敏鹏綦宏志万柏坤
Owner TIANJIN UNIV
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