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Method for eliminating myoelectric artifact in single-channel electroencephalogram signal

An EEG signal, single-channel technology, applied in the preprocessing of EEG signals, automatically identifying and eliminating EMG artifacts, in the research field of human brain-related diseases and human brain function, can solve the problem of high computational complexity, denoising Insufficient effect and other problems, to achieve the effect of good separation and excellent denoising effect

Pending Publication Date: 2019-03-19
HEFEI UNIV OF TECH
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Problems solved by technology

However, the computational complexity of ensemble empirical mode decomposition is too high, and the denoising effect is not good in many cases.

Method used

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  • Method for eliminating myoelectric artifact in single-channel electroencephalogram signal
  • Method for eliminating myoelectric artifact in single-channel electroencephalogram signal
  • Method for eliminating myoelectric artifact in single-channel electroencephalogram signal

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Embodiment Construction

[0038] Such as figure 1 As shown, the method for eliminating EMG artifacts in single-channel EEG signals is: first decompose the single-channel EEG signals by singular spectrum analysis, and obtain a multidimensional matrix composed of signal components. Then, independent vector analysis is performed on the multidimensional matrix, and the independent components containing myoelectric artifacts are removed by using the autocorrelation coefficient as a threshold index. Finally, reconstruct the data to obtain a clean single-channel EEG signal.

[0039] In order to verify the denoising effect of the present invention through experiments, the following will take semi-simulated EEG signals and real EEG signals as examples, and illustrate the specific implementation of EMG artifact removal in single-channel EEG signals in conjunction with the accompanying drawings .

[0040] 1. Semi-analog EEG signal

[0041] This section will introduce the specific implementation of the present ...

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Abstract

The invention discloses a method for eliminating myoelectric artifact in a single-channel electroencephalogram signal, which is characterized by comprising the following steps: 1, decomposing the single-channel electroencephalogram signal by using singular spectrum analysis to obtain a multidimensional signal component matrix; 2, performing blind source separation on the signal component matrix byusing independent vector analysis to obtain a plurality of independent components; 3, setting up the threshold of the self-correlation, and detecting independent components containing myoelectric artifacts and setting the independent components to zero; and 4, performing blind source separation inverse transformation on the partial zero-set independent components, and reconstructing to obtain a clean single-channel electroencephalogram signal. The invention can achieve the removal of myoelectric artifacts in single-channel electroencephalogram signal and has important significance for the subsequent analysis of the electroencephalogram signal.

Description

technical field [0001] The invention belongs to the technical field of EEG signal processing, and specifically relates to a new method for automatically identifying and eliminating EMG artifacts from single-channel EEG signals based on singular spectrum analysis and independent vector analysis, and is mainly used in the prediction of EEG signals. treatment, and research on human brain-related diseases and human brain functions. Background technique [0002] EEG signals are the spontaneous and rhythmic electrophysiological activities of brain nerve cell groups, including comprehensive external manifestations such as ion exchange and metabolism. The EEG signals directly collected by the EEG equipment from the scalp are often weak, so the EEG signals collected by the EEG equipment generally need to be amplified and processed by amplifiers. EEG refers to the graph with certain waveform information formed by the amplified and processed EEG signal. Due to its high temporal resol...

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Application Information

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IPC IPC(8): A61B5/0476
CPCA61B5/7203A61B5/7225A61B5/369
Inventor 成娟李路畅徐雪远陈勋宋仁成陈强刘爱萍
Owner HEFEI UNIV OF TECH
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