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

Mental load level recognition method

A technology of mental load and identification method, applied in medical science, sensors, diagnostic recording/measurement, etc., can solve the problems of time lag, difficult driver's mental load evaluation, etc., and achieve the effect of high accuracy

Inactive Publication Date: 2017-07-04
SOUTHWEST JIAOTONG UNIV
View PDF1 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the various methods in the prior art, subjective evaluation and behavioral performance evaluation have a time lag with the behavioral state, and it is difficult to be used for real-time evaluation of the driver's mental load

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
  • Mental load level recognition method
  • Mental load level recognition method
  • Mental load level recognition method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0056] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and examples.

[0057] This embodiment provides a method for identifying a mental load level.

[0058] figure 1 It is a schematic flowchart of a method for identifying a mental load level in an embodiment of the present invention. Such asfigure 1 As shown, the identification method of the mental load level in the embodiment of the present invention mainly includes the following steps:

[0059] Step 11, collecting EEG signals through a plurality of electrodes, and recording reaction time parameters corresponding to the EEG signals.

[0060] In the technical solution of the present invention, in order to test the driver's simple reaction time to the unexpected time, it is necessary to carry out corresponding tests on the tested persons (for example, volunteers), so as ...

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 mental load level recognition method. The mental load level recognition method includes: acquiring EEG signals through a plurality of electrodes, and recording reaction time parameters corresponding to the EEG signals; extracting EEG signal parameters from the acquired EEG signals; selecting a preset number of EEG signal parameters as a driving mental load feature index from the acquired EEG signal parameters; establishing an SVM recognition model on the basis of the driving mental load feature index; and recognizing the mental load level according to the SVM recognition model. The mental load level recognition method can achieve dynamic real-time recognition of the mental load level of a driver.

Description

technical field [0001] The invention relates to stress detection technology, in particular to an identification method of mental load level. Background technique [0002] The widespread use of in-vehicle information systems (eg, GPS navigation, real-time communication, in-vehicle audio and video systems, etc.) and the increased complexity of traffic control information increase the mental load of drivers. High mental load conditions will cause the driver to prolong the reaction time to sudden traffic incidents and reduce the recognition rate of surrounding traffic incidents, which will cause reaction operation errors and affect driving safety. Therefore, the effective identification of the driver's mental load level is a key issue in the study of driving behavior. [0003] At present, extensive research has been carried out on the mental load of drivers at home and abroad. The research results show that traffic environment factors such as traffic flow, traffic signs, and ro...

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): A61B5/18A61B5/0476
CPCA61B5/168A61B5/18A61B5/7271A61B2503/22A61B5/316A61B5/369
Inventor 郭孜政张骏
Owner SOUTHWEST JIAOTONG 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