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

Multi-brain-computer interface method for three characteristics of SSVEP (Steady State Visual Evoked Potential), blocking and P300

A computer interface and EEG technology, applied in the field of SSVEP and blocking and P300 three-characteristic multi-brain-computer interface, can solve the problems of low execution efficiency, correct judgment rate and unhelpful information transmission rate, so as to improve the system information transmission rate , considerable social and economic benefits

Active Publication Date: 2012-11-28
TIANJIN UNIV
View PDF2 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The advantage of this system is to use the SSVEP characteristic signal as the state switch of the subject, but it is still not beneficial to improve the judgment accuracy and information transmission rate of the task.
[0006] In addition, traditional brain-computer interfaces usually have only one system, so the execution efficiency is generally low

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
  • Multi-brain-computer interface method for three characteristics of SSVEP (Steady State Visual Evoked Potential), blocking and P300
  • Multi-brain-computer interface method for three characteristics of SSVEP (Steady State Visual Evoked Potential), blocking and P300
  • Multi-brain-computer interface method for three characteristics of SSVEP (Steady State Visual Evoked Potential), blocking and P300

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0019] The present invention designs a multi-mode brain-computer interface (BCI) stimulation paradigm based on the three characteristics of SSVEP, SSVEP blocking and P300, effectively combines the SSVEP characteristics, SSVEPB characteristics and P300 characteristics, and establishes multiple different modes for parallel operation The BCI system expands the BCI command set and greatly improves the information transmission rate of BCI.

[0020] The technical process is: design a new paradigm experiment, build the EEG signal acquisition device required for the experiment, and then collect the operator’s EEG signal data under the guidance of the experimental system, store it and then perform certain preprocessing and feature extraction , and finally use linear discriminant analysis to classify and calculate its judgment accuracy rate and information transmission rate.

[0021] The present invention proposes a new multi-PHBCI parallel system, which can simultaneously induce SSVEP,...

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 relates to the field of medical equipment in order to improve the transmission rate of system information greatly. The invention adopts the technical scheme that the multi-brain-computer interface method for three characteristics of SSVEP (Steady State Visual Evoked Potential), blocking and P300 comprises the following steps: adopting a computer and an electroencephalogram acquisition system including an electroencephalogram electrode, an electroencephalogram amplifier and an electroencephalogram filter, wherein the computer further comprises an EEG (Electroencephalo-Graph) analytical program and a stimulation and induction user interface; acquiring electroencephalogram data of multiple channels by using the electroencephalogram acquisition system; generating an electroencephalogram signal from cerebral cortex, detecting the electroencephalogram signal by using the electroencephalogram electrode, amplifying by using the electroencephalogram amplifier, and filtering and inputting to the computer; and carrying out subsequent data process on the acquired electroencephalogram data to extract corresponding SSVEP, SSVEP blocking and P300 characteristic signals, thus the characteristics are applied to mode recognition of experimental tasks. The multi-brain-computer interface method is mainly applied to the design and manufacturing of the medical equipment.

Description

technical field [0001] The invention relates to the field of medical devices, in particular to SSVEP, blocking and P300 three-characteristic multi-brain-computer interface methods adopted in medical devices. Background technique [0002] When a normal person is stimulated by flickering at a certain frequency (generally greater than 6Hz), the corresponding EEG will have a response consistent with the stimulation frequency or its harmonics. This response is the so-called steady-state visual evoked potential; P300 is in the A positive peak appears in the EEG around 300ms after the target stimulation; SSVEP block (SSVEPB) is a phenomenon in which the energy of the SSVEP signal that appears in the new paradigm of SSVEP and P300 fusion is suppressed when the target stimulation occurs. [0003] The definition of BCI given by the first Brain-Computer Interface (BCI) International Conference is: "BCI is a communication control system that does not depend on the normal output channels...

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
Inventor 许敏鹏马岚陈龙付兰安兴伟綦宏志万柏坤明东
Owner TIANJIN 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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com