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

Method for making electroencephalogram target judgment with assistance of machine vision

A machine vision and target technology, applied in the direction of instruments, computer components, character and pattern recognition, etc., can solve the problems of low false alarm rate, P300 detection algorithm accuracy decline, etc., to achieve the effect of improving accuracy and effect

Active Publication Date: 2016-08-03
THE PLA INFORMATION ENG UNIV
View PDF4 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The invention overcomes the problem in the prior art that the specific meaning of the target image will lead to changes in the latency of the P300 components, resulting in a decrease in the accuracy of the single-trial P300 detection algorithm, and provides a machine vision-assisted brain with high accuracy and low false alarm rate. Method of Electric Target Judgment

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
  • Method for making electroencephalogram target judgment with assistance of machine vision
  • Method for making electroencephalogram target judgment with assistance of machine vision
  • Method for making electroencephalogram target judgment with assistance of machine vision

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0016] The following is a further description of the method for machine vision-assisted EEG target judgment of the present invention with reference to the accompanying drawings and specific embodiments: It contains the following steps, step (1), while the subject is watching the RSVP image sequence, the EEG signal acquisition equipment collects The EEG signal of the test; step (2), determine the variation error of the P300 component latency of the subject through the EEG signal corresponding to the target image; step (3), use the single-trial P300 detection algorithm to generate the image Detect the P300 component of the EEG signal, and use the P300 component to locate the position of the target image in the image sequence; step (4), combining the latency change error determined in step (2) with the single-trial detection algorithm in step (3) Determine the target candidate image; step (5), use machine vision to identify and classify the target candidate images, and count the ca...

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 method for making electroencephalogram target judgment with assistance of machine vision. With the method, a problem that the single-trial P300 detection algorithm precision is reduced because of changing of a P300 component incubation period due to specific implication of a target image can be solved. The method comprises: (1), an electroencephalogram signal collection device collects a tested electroencephalogram signal; (2), a changing error of a tested P300 component incubation period is determined; (3), a position of a target image in an image sequence is localized based on the P300 component; (4), a target candidate image is determined by combining the incubation period changing error determined at the step (2) and the target image position determined by the single-trail detection algorithm at the step (3); and (5), identification and classification are carried out on the target candidate image by using machine vision, and an image type with the highest occurrence frequency is used as a concerned target image type on trial. The method has advantages of high accuracy and low false alarm rate.

Description

Technical field [0001] The invention relates to an image retrieval method that combines machine vision and EEG signals, and particularly relates to a method for assisting EEG target judgment by machine vision. Background technique [0002] In image retrieval technology, how to find a specific image is a difficult problem. Through natural evolution, the human brain has the ability to quickly and deeply grasp images. Introducing the visual system of the human brain into the existing image retrieval technology to improve the results of image retrieval is a research direction in the current image retrieval system. The pictures are presented using the rapid sequence presentation paradigm (RSVP). The pictures are quickly presented to the subjects at a speed of 5-12 frames per second. The subjects watch these pictures and collect the EEG signals generated by the subjects while watching the pictures. When the subjects see the target picture of interest, a specific component is induced ...

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): G06K9/62
CPCG06V2201/07G06F18/2178
Inventor 童莉曾颖林志敏王林元陈健张驰王彪蒋静芳巫群健
Owner THE PLA INFORMATION ENG 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