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

Multi-channel evoked potential detection method and system based on independent component analysis

An independent component analysis and evoked potential technology, which is applied in the field of biomedical information processing, can solve the problems of long time consumption and low efficiency, and achieve the effect of overcoming long time consumption, high efficiency and high detection sensitivity

Inactive Publication Date: 2021-07-13
SHENZHEN TECH UNIV
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Traditional methods generally use superposition averaging technology to remove background EEG signals and interference signals. In this way, the number of superimposed averages needs to be determined according to the signal-to-noise ratio of the recorded background EEG signals, which usually requires dozens or even thousands of averaging times. It takes a long time to determine whether the signal to be tested contains evoked potentials, and the efficiency is 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-channel evoked potential detection method and system based on independent component analysis
  • Multi-channel evoked potential detection method and system based on independent component analysis
  • Multi-channel evoked potential detection method and system based on independent component analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0042] refer to figure 1 , the present embodiment provides a multi-channel evoked potential detection method based on independent component analysis, which is executed by a microprocessor, an embedded processor or a computer terminal, and the method includes the following steps:

[0043] S1. Collect the multi-channel EEG signals of the subject under the action of repetitive stimulation; the repetitive stimulation consists of multiple identical transient stimulation units serially and repeatedly arranged. In this embodiment, the repetitive stimulation consists of N serial Stimulation unit composition.

[0044] S2. Perform preprocessing on the collected multi-channel EEG signals; in this step, the preprocessing includes at least one of filtering processing, interpolation processing and removing abnormal data. The filtering process refers to performing band-pass filtering on the multi-channel EEG signal, and the specific pass-band range can be set according to the actual signal ...

Embodiment 2

[0071] This embodiment is a detailed example of the first embodiment of the method. Specifically, the NeuroScan (SynAmps2) EEG recording system is used to collect multi-channel EEG signals of the subject under repeated stimulation. In this embodiment, the repetitive stimulation consists of a plurality of identical transient stimulation units arranged repeatedly in series, specifically, the repetitive stimulation consisting of short pure tones with a duration of 50 ms is used, the stimulation interval is 1.01 s, and the number of stimulations is about 500. During the test, the test electrode is placed in the following way: adopt the international 10-20 system, select 36 positions to place the electrodes, the 36 positions selected here are: FT7, FC5, FC3, FC1, FCZ, FC2, FC4, FC6, FT8, T7, C5, C3, C1, CZ, C2, C4, C6, T8, TP7, CP5, CP3, CP1, CPZ, CP2, CP4, CP6, TP8, P7, P5, P3, P1, PZ, P2, P4, P6, P8, wherein, the reference electrode is at the midpoint of CZ and CPZ, and the groun...

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 multi-channel evoked potential detection method and system based on independent component analysis. The method includes: collecting and preprocessing the multi-channel EEG signals of the subject under repeated stimulation; Perform independent component analysis on the electrical signal to obtain multiple independent components; take the start time of the stimulation unit as the benchmark, obtain the independent cost sample of each stimulation unit; perform time-domain superposition averaging on the independent component samples to obtain the cost of each independent component Average evoked potential; filter and eliminate independent component samples according to the set criteria; select the test sample, calculate the total evoked energy gain of the test sample and the total evoked energy gain of the average sample of the test sample, and judge whether there is a stimulus unit in the selected test sample evoked potential. The invention has fast calculation speed, high efficiency and high detection sensitivity, and can be widely used in the detection field of weak evoked potentials.

Description

technical field [0001] The invention relates to the field of biomedical information processing, in particular to a multi-channel evoked potential detection method and system based on independent component analysis. Background technique [0002] During the acquisition and processing of biomedical signals, compared with the background EEG signals and interference signals of 20-150 μV, the evoked potential signal is very weak, mainly in the range of 0.1-10 μV. Traditional methods generally use superposition averaging technology to remove background EEG signals and interference signals. In this way, the number of superimposed averages needs to be determined according to the signal-to-noise ratio of the recorded background EEG signals, which usually requires dozens or even thousands of averaging times. It takes a long time to determine whether the signal to be tested contains evoked potentials, and the efficiency is low. [0003] Glossary [0004] ICA: The full name is Independ...

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 Patents(China)
IPC IPC(8): A61B5/00A61B5/377A61B5/372
CPCA61B5/7203A61B5/7235A61B5/377
Inventor 王涛谭小丹林霖
Owner SHENZHEN TECH 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