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

An independent component analysis and evoked potential technology, applied in the field of biomedical information processing, can solve problems such as low efficiency and long time consumption

Inactive Publication Date: 2019-03-26
SHENZHEN TECH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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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

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  • 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

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Embodiment 1

[0045] 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:

[0046] 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.

[0047] 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

[0074] 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...

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Abstract

The invention discloses a multi-channel evoked potential detection method and system based on independent component analysis. The method comprises the following steps of: collecting multi-channel electroencephalogram signals of an subject under repetitive stimulation and pretreating, carrying out independent component analysis on the pretreated multi-channel electroencephalogram signals to obtaina plurality of independent components; obtaining an independent cost sample of each stimulation unit by taking the starting time of the stimulation unit as a reference; carrying out time domain superposition averaging on the independent component samples to obtain an average evoked potential of each independent component sample; screening and eliminating the independent component samples accordingto a set criterion; and selecting detection samples, calculating the total induced energy gain of the detection samples and the total induced energy gain of the average sample of the detection samples, and judging whether the selected detection samples have an evoked potential caused by the an stimulation unit or not. The method has the advantages of high calculation speed, high efficiency and high detection sensitivity, and can be widely applied to the field of weak evoked potential detection.

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

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Application Information

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IPC IPC(8): A61B5/00A61B5/0484
CPCA61B5/7203A61B5/7235A61B5/377
Inventor 王涛谭小丹林霖
Owner SHENZHEN TECH UNIV
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