Electrocardiograph and respiratory signal synchronous characteristic based emotion detection method

A respiratory signal and detection method technology, applied in the direction of diagnostic signal processing, evaluation of respiratory organs, psychological devices, etc., can solve problems such as the accuracy rate needs to be improved, interference, etc.

Active Publication Date: 2016-12-21
TIANJIN UNIV
View PDF5 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the commonly used physiological signals include electroencephalogram signal (EEG), electrocardiogram signal (ECG), electrodermal signal, respiratory signal (RSP), electromyographic signal (EMG), pulse signal, etc., but the current research i...

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
  • Electrocardiograph and respiratory signal synchronous characteristic based emotion detection method
  • Electrocardiograph and respiratory signal synchronous characteristic based emotion detection method
  • Electrocardiograph and respiratory signal synchronous characteristic based emotion detection method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0043] The present invention first performs signal preprocessing on ECG and RSP, and extracts the HRV signal from the ECG signal, then calculates the time domain synchronization characteristics and phase synchronization characteristics of the ECG and RSP signals, and the frequency domain synchronization characteristics of HRV and RSP, These features are fused together to form an emotional feature matrix, and the Fisher separability analysis is used to evaluate the separability of each feature, and the feature weights are adjusted accordingly. Finally, an emotion recognition model is constructed through a support vector machine to accurately and objectively Do emotion recognition.

[0044] figure 1 It is a flow chart of the method of the present invention, and the five stages of the emotional state recognition method based on the synchronization of ECG and respiratory signals of the present invention are described below.

[0045] (1) Data collection stage: the data collection ...

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 relates to an electrocardiograph and respiratory signal synchronous characteristic based emotion detection method. The method includes: acquiring ECG (electrocardiograph) signals and respiratory signals; preprocessing; extracting characteristics including 1) time domain synchronous characteristics, 2) frequency domain synchronous characteristics and 3) phase lock valves; assessing separability of each characteristic according to a Fisher discriminant ratio, calculating to finally obtain FDR (Fisher discriminant ratio) values of five characteristics, and distributing corresponding weight value wi to each characteristic according to the FDR values; adopting a SVM (support vector machine) for establishing an emotion recognition model to recognize a current emotion state of a user. The electrocardiograph and respiratory signal synchronous characteristic based emotion detection method has the advantage that accurate real-time emotion monitoring can be realized.

Description

technical field [0001] An emotion detection method based on the synchronization characteristics of ECG and respiratory signals is proposed. The invention relates to an emotional state identification method that can be used in the diagnosis and curative effect evaluation of clinical emotional disorders, and emotional neurofeedback regulation. Background technique [0002] Emotion is a comprehensive state produced by people whether objective things meet their own needs. As a high-level function of the human brain, it ensures the survival and adaptation of organisms, and affects human learning, memory and decision-making to varying degrees. In people's daily work and life, the role of emotion is everywhere. Negative emotions can affect our physical and mental health, reduce work quality and efficiency, and in severe cases can cause mental illness (such as depression, autism, etc.), and also cause serious work mistakes. Studies have shown that the long-term accumulation of ne...

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): A61B5/16A61B5/0402A61B5/08
CPCA61B5/08A61B5/165A61B5/72A61B5/7235A61B5/7246A61B5/318
Inventor 刘爽明东仝晶晶郭冬月安兴伟许敏鹏綦宏志何峰周鹏
Owner TIANJIN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap