Brain machine interface system based on human face recognition specific wave N170 component

A face recognition, brain-computer interface technology, applied in character and pattern recognition, computer parts, mechanical mode conversion, etc., can solve problems such as long distance, achieve the effect of high speed, low error rate and high recognition effect

Inactive Publication Date: 2009-01-07
BEIJING NORMAL UNIVERSITY
View PDF2 Cites 31 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The above-mentioned system has more or less problems in the correct rate of judgment and real-time effect. Although the correct

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
  • Brain machine interface system based on human face recognition specific wave N170 component
  • Brain machine interface system based on human face recognition specific wave N170 component
  • Brain machine interface system based on human face recognition specific wave N170 component

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] figure 2 Shown is a schematic diagram of the brain-computer interface system based on the steady-state visual evoked potential.

[0028] (1) Picture stimulator

[0029] The picture stimulator presents pictures of faces and objects, and the working state of the human brain is collected by the scalp EEG collector, processed and analyzed by the N170 detector, and converted into picture classification control instructions. Picture stimulators in the system such as Figure 5 As shown, the face or object picture stimuli were randomly presented at intervals of 500 milliseconds, and the order of presentation was random, and each picture was presented for 500 milliseconds.

[0030] (2) Scalp EEG signal collector

[0031] The role of the scalp EEG signal collector is to collect EEG signals that can reflect the working state of the user's brain. The electrodes can detect the potential of the scalp surface, but the multi-channel EEG signals collected by the scalp electrodes are ...

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 present invention relates to a brain-machine interface system based on face recognition specific wave N170 component, which implements sorting of facial pictures and object pictures, and comprises a picture stimulator, a cortical electric signal collector, a face recognition specific wave N170 detector, and a picture sorter. Pictures to be sorted are presented by the visual picture stimulator as visual stimulations to a user, and the cortical electric signals of the user generated in response are recorded and subjected to amplification and A/D conversion, and then processed and analyzed by the face recognition specific wave N170 detector, whereby a determination is made whether the collected cortical electric signals contain specific wave N170 component related to facial picture stimulation, and accordingly, the cortical electric signals are transformed into picture sorting control commands for identifying facial pictures and object pictures. The advantages of the present invention are: the present invention utilizes the specific cortical electric signal N170 component generated in the facial picture recognition process in response to facial picture stimulations, and employs an effective online feature extraction and sorting algorithm in the cortical electric signal analyzer; therefore, the discrimination ratio of the system is increased. The present invention provides a novel means for persons who suffer from dyskinesia but can think normally to communicate with and control the external environment.

Description

technical field [0001] The present invention relates to a brain-computer interface system based on the N170 component of the specific wave for face recognition, and specifically refers to a brain-computer interface system device that utilizes the N170 specific component of face recognition in human brain scalp EEG to realize image classification. Through this system, face pictures and object pictures can be classified into different categories. In the whole process, there is no need for complex image processing of the pictures to be classified, and no physical and language actions are required. It belongs to the combined application of the field of cognitive neuroscience and the field of signal processing technology, and belongs to the field of automatic control technology. Background technique [0002] Brain-computer interface technology, formed in the 1970s, is a new human-computer interface technology whose main goal is to issue commands from the cerebral cortex to the ou...

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): G06F3/01G06K9/62A61B5/0476
Inventor 张家才尹恺姚力徐雅琴张行武进
Owner BEIJING NORMAL UNIVERSITY
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