Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Emotion recognition method and system

An emotion recognition and to-be-recognized technology, applied in the field of emotion recognition, can solve the problem of low accuracy of emotion recognition

Inactive Publication Date: 2019-06-11
TAIYUAN UNIV OF TECH
View PDF6 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the nonlinearity and non-stationarity of emotional EEG signals and the complexity of the interaction of various brain regions in the process of emotional cognition, a single feature or a simple combination of several features cannot effectively represent the differences in EEG induced by different emotions. , the accuracy of emotion recognition is not high

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Emotion recognition method and system
  • Emotion recognition method and system
  • Emotion recognition method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0106] figure 1 It is a flow chart of an emotion recognition method provided by an embodiment of the present invention. like figure 1 As shown, an emotion recognition method, including:

[0107] Step 101: Randomly play speech clips of various emotion types to the user, collect the user's EEG signals in each emotion type speech clip, and obtain the EEG signals to be trained. Emotion types include Sad, Angry, Happy, Surprised.

[0108] Step 102: Extract the EEG signal features to be trained.

[0109] Before extracting the features of the EEG signal to be trained, the acquired EEG signal to be trained is preprocessed, and the processing method is the same as the preprocessing method in step 106 .

[0110] The EEG signal features to be trained include: time-frequency domain features to be trained, nonlinear features to be trained, and brain network attribute features to be trained; the time-frequency domain features to be trained are based on wavelet decomposition of the EEG s...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an emotion recognition method and system. The method comprises the steps of acquiring an electroencephalogram signal to be recognized; extracting to-be-identified time-frequency domain characteristics, to-be-identified nonlinear characteristics and to-be-identified brain network attribute characteristics; wherein the to-be-identified time-frequency domain feature is a wavelet entropy calculated according to a wavelet decomposition coefficient of the to-be-identified electroencephalogram signal; wherein the to-be-identified nonlinear feature comprises a power spectrum density obtained by performing discrete Fourier transform on the to-be-identified electroencephalogram signal and a Hurst index obtained by performing average error calculation on the to-be-identified electroencephalogram signal; wherein the attribute characteristics of the to-be-identified brain network reflect the correlation among the to-be-identified electroencephalogram signals; and carrying out emotion recognition on the to-be-recognized electroencephalogram signal features by adopting a trained support vector classifier. The method and the system provided by the invention have the advantage that the emotion recognition accuracy can be improved.

Description

technical field [0001] The invention relates to the technical field of emotion recognition, in particular to an emotion recognition method and system. Background technique [0002] Emotion is a psychological and physiological reaction process induced by external stimuli. Correct and effective emotion recognition is an important guarantee for people's daily life and communication, and it is also a key problem to be solved in the realization of advanced artificial intelligence. Traditional emotion recognition is mainly based on external behaviors such as facial expressions, voice intonation, and gestures. However, the emotional characteristics reflected in these external expressions are highly subjective and easy to be concealed or disguised. With the development of sensing technology, emotion recognition based on real-time acquisition of electrophysiological signals, such as EEG, ECG, and EMG, is more reliable and effective, especially EEG signals can objectively reflect the...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06K9/00G06K9/62
Inventor 陈桂军张雪英李凤莲孙颖黄丽霞王杰
Owner TAIYUAN UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com