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

Driver fatigue and emotion evaluation method based on multi-source physiological information

A driver fatigue and physiological information technology, which is applied in the field of driver fatigue and emotional evaluation based on multi-source physiological information, can solve the problems of high error rate and poor recognition effect, and achieve improved accuracy, emphasis on comprehensiveness, and classification good effect

Inactive Publication Date: 2018-03-23
YANSHAN UNIV
View PDF9 Cites 38 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The current evaluation methods for driver fatigue almost use a single fatigue detection index (EEG or ECG), which has a high error rate, and the recognition effect is not good using traditional classification methods (such as parameter estimation and fuzzy regression)

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
  • Driver fatigue and emotion evaluation method based on multi-source physiological information
  • Driver fatigue and emotion evaluation method based on multi-source physiological information
  • Driver fatigue and emotion evaluation method based on multi-source physiological information

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0036] The present invention will be further described below in conjunction with accompanying drawing:

[0037] Such as figure 1 , 5 Shown, the inventive method comprises the following steps:

[0038] Step 1, use MP150WSW to synchronously collect EEG signals, ECG signals and EMG signals, and collect head posture information through the inertial sensor module;

[0039] Step 2, use the MP150WSW device data processing software to preprocess the collected EEG signals, ECG signals and EMG signals, and perform feature extraction on the physiological signals;

[0040] Step 3, use the EEG, ECG, EMG and attitude signals as the input of the fuzzy neural network, and the output is the fatigue and emotional state of the driver;

[0041] Step 4, based on the neural network evaluation model, the genetic algorithm is used to continuously learn the driver's evaluation indicators, and the rules and methods for driver fatigue and emotional evaluation are extracted.

[0042] Such as figure 2...

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 driver fatigue and emotion evaluation method based on multi-source physiological information. The method comprises the following steps of 1, simultaneously collecting a driver's EEG, ECG, EMG and attitude signals; 2, performing pretreatment and feature extraction on the physiological signals; 3, building a fuzzy neural network evaluation model to achieve driver fatigue and emotion evaluation; and 4, based on the evaluation model, using genetic algorithms for continuously learning the driver's evaluation index, extracting rules and methods of driver fatigue and emotionevaluation, and improving the evaluation accuracy. The method emphasizes the comprehensiveness of decision information and the advanced nature of a classification method, greatly improves the accuracy of driver fatigue and emotion evaluation, and reduces the probability of occurrence of traffic accidents.

Description

technical field [0001] The invention relates to the field of automobile assisted driving, in particular to a method for evaluating driver fatigue and emotion based on multi-source physiological information. Background technique [0002] With the rapid increase of China's car ownership in recent years, road traffic safety issues and driver comfort experience have become the focus of society. According to incomplete statistics, nearly 100,000 people lose their lives due to vehicle traffic accidents in my country every year, ranking first in the world for 10 consecutive years. Traffic accidents have become the most casualties in various accidents in the country. Sudden illnesses and abnormal driving conditions such as road rage accounted for more than 35% of traffic accidents, seriously threatening the safety of life and property of the general social groups. Therefore, it is of great significance to monitor and adjust physiological states such as fatigue and emotion that affec...

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
Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0402A61B5/0476A61B5/0488A61B5/11A61B5/16
CPCA61B5/1116A61B5/165A61B5/72A61B5/7264A61B5/7271A61B2503/22A61B5/316A61B5/318A61B5/369A61B5/389
Inventor 谢平齐孟松邹策张艺滢孙凯刘兆军程生翠杜义浩何群
Owner YANSHAN UNIV
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