Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Brain-computer interface method based on multi-modal signal identification

A brain-computer interface and signal recognition technology, applied in the field of brain-computer interface, can solve problems such as dependence and easy generation of wrong commands

Pending Publication Date: 2022-03-25
UNIV OF SCI & TECH LIAONING
View PDF9 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Aiming at the deficiencies of the prior art, the present invention provides a brain-computer interface method based on multimodal signal recognition, which solves the problem that the current multimodal brain-electrical interface technology mainly relies on visual aids, and it is easy to generate wrong commands in the idle state. The problem

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-computer interface method based on multi-modal signal identification
  • Brain-computer interface method based on multi-modal signal identification
  • Brain-computer interface method based on multi-modal signal identification

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0033] Such as Figure 1-4 As shown, the embodiment of the present invention provides a brain-computer interface method based on multimodal signal recognition, including a brain-computer interface system. The brain-computer interface system includes a host 100, a display screen 200, and an eye tracker 300. The host 100 includes a microprocessor device 101, brain wave signal acquisition module 102, brain wave signal analysis module 103, ear clip-type infrared heart rate acquisition module 104, heart rate signal analysis module 105, display screen 200 includes a display module 201, a positioning capture module 202, and a data feedback module 203.

[0034] The brain wave signal acquisition module 102 is used to collect signals, the brain wave signal acquisition module 102 selects a non-invasive head-mounted electrode sheet, the microprocessor 101 is electrically connected to the display screen 200, and the eye tracker 300 is electrically connected to the display module 201 of the ...

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 provides a brain-computer interface method based on multi-modal signal identification, and relates to the technical field of brain-computer interfaces. The brain-computer interface method based on multi-modal signal identification comprises the following steps: S1, starting a device to collect brain wave signals; s2, analyzing the brain wave signals and generating corresponding action consciousness; s3, a display screen displays whether the action awareness starts an interface or not; s4, the user selects whether action awareness is started or not through sight line concentration, if yes, the next step is executed, and if not, an action awareness command is not executed; s5, the display screen enters a detailed selection interface, and the user determines the motion consciousness by centralizing on the specific selection interface; s6, when the user enters a motion awareness detailed selection interface, the motion awareness is finally confirmed by analyzing the heart rate fluctuation condition of the user. Through the method designed by the invention, the brain wave signals of the user can be accurately understood through three modes, meanwhile, error signals are not generated, and the practicability is extremely high.

Description

technical field [0001] The invention relates to the technical field of brain-computer interface methods, in particular to a brain-computer interface method based on multimodal signal recognition. Background technique [0002] The brain-computer interface is a kind of information exchange and control between the human brain and computers or other communication devices by collecting and analyzing the signals of the cerebral cortex, and converting them into instructions to control peripheral equipment. It does not depend on the conventional human brain. Normal output channel. Using the human brain to produce different responses to different things or cognitive activities, so as to obtain different types of EEG signals. The conversion of control instructions is realized by amplifying, filtering, collecting, feature extraction, and classification of EEG signals. Currently, there are two methods of EEG acquisition, implantable and non-implantable. The former needs to implant el...

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): G06F3/01
CPCG06F3/015Y02D10/00
Inventor 史添玮任玲崔文华张文宇赵骥张玉军代红强姣凤常桄铭
Owner UNIV OF SCI & TECH LIAONING
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
Eureka Blog
Learn More
PatSnap group products