Dynamic brain network analysis method for emotion awakening degree

An analysis method and brain network technology, applied in the field of EEG signal analysis, can solve the problem of clear enough observation during the experimental stimulation process

Active Publication Date: 2021-03-09
HANGZHOU DIANZI UNIV
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AI Technical Summary

Problems solved by technology

However, the establishment of traditional brain networks is often static, which is not enough for us to have a clear enough observation of the experimental stimulation process

Method used

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  • Dynamic brain network analysis method for emotion awakening degree
  • Dynamic brain network analysis method for emotion awakening degree
  • Dynamic brain network analysis method for emotion awakening degree

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Embodiment Construction

[0038] In order to effectively observe the emotionally stimulated brain state, the present invention mainly improves on the construction and analysis of the brain functional brain network. The embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings: this embodiment is implemented on the premise of the technical solution of the present invention, and provides detailed implementation methods and specific operating procedures.

[0039] The dynamic brain network analysis method of positive emotions in the arousal dimension, the overall process is as follows figure 1 Shown, its specific embodiment comprises the following steps:

[0040] Step 1, collecting EEG signals under different emotional stimuli. 32 volunteers were selected for 40 visual and auditory stimulation experiments, and EEG signals of 32 channels were collected simultaneously. At the end of the experiment, each subject had to score 1 to 9 points for the st...

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Abstract

The invention discloses a dynamic brain network analysis method for an emotion awakening degree. Data is segmented by adopting a sliding time window, and a brain function network is established through a transfer entropy. Segmented brain networks are connected into a dynamic brain network according to a time sequence, and the dynamic brain network is used for displaying detailed dynamic changes ofa subject in an experimental stimulation process. In order to ensure that dynamic connection is real and reliable, clustering and substitution sequences are used for testing and analysis. Finally, data is optimized by using optimally calculated feature-channel specification information, and an activity level is evaluated, so that a result is clearer. Guidance and a basis are provided for searching for potential important stimulation segments. Compared with a traditional static brain network, the method has the advantages that the brain function network is established in a more reasonable andscientific manner, the changes of a brain state in the experimental stimulation process can be observed and analyzed more carefully, and a network structure and result analysis can be effectively simplified through proposed features.

Description

technical field [0001] The invention belongs to the field of biological signal processing, and relates to an analysis method of EEG signals for constructing a dynamic brain network under emotional stimulation of different arousal degrees. [0002] technical background [0003] Affective Computing (AC) is attracting more and more attention. It can help computers recognize and analyze people's emotions, so as to establish a good human-computer interaction relationship. Affective computing is related to sentiment analysis and emotion recognition of human emotions. Among them, sentiment analysis is an important part, and the brain plays a major role in the generation and expression of human emotions. Electroencephalogram (Electroencephalogram, EEG) is the signal generated by the spontaneous or rhythmic activity of brain nerve groups recorded by electrodes, which reflects the potential changes of nerve cell groups in brain functional areas. And the EEG signal has the characteris...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/369A61B5/374A61B5/16A61B5/00A61B5/378A61B5/38
CPCA61B5/165A61B5/7203A61B5/725A61B5/7235A61B5/7253
Inventor 高云园曹震黄金诚翟家豪佘青山孟明
Owner HANGZHOU DIANZI UNIV
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