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

Depression recognition method and device based on electroencephalogram signals, terminal and medium

An electroencephalogram signal and identification method technology, applied in the computer field, can solve problems such as low efficiency and long analysis time, and achieve the effect of improving efficiency and shortening time

Pending Publication Date: 2021-09-17
北京脑陆科技有限公司
View PDF9 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method of diagnosing depression through EEG signals has the problems of long analysis time and low efficiency

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
  • Depression recognition method and device based on electroencephalogram signals, terminal and medium
  • Depression recognition method and device based on electroencephalogram signals, terminal and medium
  • Depression recognition method and device based on electroencephalogram signals, terminal and medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0019] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, not to limit the present application.

[0020] It should be noted that although the functional modules are divided in the schematic diagram of the device, and the logical sequence is shown in the flowchart, in some cases, it can be executed in a different order than the module division in the device or the flowchart in the flowchart. steps shown or described.

[0021] In order to make the purpose, technical solution and advantages of the present application clearer, the implementation manners of the present application will be further described in detail below in conjunction with the accompanying drawings.

[0022] According to...

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 a depression recognition method and device based on electroencephalogram signals, a terminal and a medium. The method comprises the following steps: acquiring an electroencephalogram signal of a tested user; determining a time domain waveform and a frequency domain waveform of the electroencephalogram signal; according to the time domain waveform and the frequency domain waveform, determining depression assessment classification for the tested user. According to the depression diagnosis method and device, depression diagnosis is carried out by extracting the electroencephalogram features, the problem that depression diagnosis is easily influenced by subjective factors in related technologies is avoided, the automatic recognition effect of depression diagnosis is achieved, and the purposes of shortening the depression recognition time and improving the depression diagnosis efficiency are achieved.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to a method, device, terminal and medium for identifying depression based on EEG signals. Background technique [0002] Depression, also known as depressive disorder, is an affective disorder with a high incidence rate. People with depression often have the classic symptoms of low mood, loss of interest and enjoyment, and low energy or fatigue. The diagnosis of depression should be mainly based on medical history, clinical symptoms, course of disease, physical examination and laboratory tests. Therefore, this diagnostic method is easily affected by subjective factors, which may easily lead to misdiagnosis and missed diagnosis. The study found that the EEG signals of patients with depression and healthy controls have different variations in parameters such as band, power, and amplitude. Therefore, in order to overcome the problem that the diagnosis of depression is eas...

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): A61B5/369A61B5/16A61B5/00
CPCA61B5/369A61B5/165A61B5/4076A61B5/7264A61B5/7267A61B5/725A61B5/7203
Inventor 张善廷王晓岸
Owner 北京脑陆科技有限公司
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