Electroencephalogram signal noise elimination method

A technology of EEG signal and noise, applied in the direction of instruments, character and pattern recognition, computer components, etc., to achieve the effect of ensuring validity and integrity

Inactive Publication Date: 2017-07-14
DONGHUA UNIV
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Problems solved by technology

[0008] The technical problem to be solved by the present invention is to provide a method for removing noise from EEG signals, which is based on the DTCWT-EEMD

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  • Electroencephalogram signal noise elimination method
  • Electroencephalogram signal noise elimination method
  • Electroencephalogram signal noise elimination method

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[0026] The present invention will be further explained below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and not to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of this application.

[0027] The embodiment of the present invention relates to a method for removing EEG signal noise based on the DTCWT-EEMD algorithm, such as figure 1 As shown, it includes the following steps: adopt EEMD algorithm to perform collective empirical mode decomposition of the collected EEG signals to obtain eigencomponents containing information of different frequency bands; the selected eigencomponents mainly contain several components of high-fr...

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Abstract

The invention relates to an electroencephalogram signal noise elimination method based on a DTCWT-EEMD algorithm. The method comprises the following steps that ensemble empirical mode decomposition is performed on the acquired electroencephalogram signals by using an EEMD algorithm so that intrinsic components including different band information are obtained; multiple components mainly including high frequency random noise of the obtained intrinsic components are selected, and the components are decomposed by using a DTCWT algorithm so that a series of wavelet coefficients corresponding to noise components are obtained; wavelet coefficient processing is performed on the wavelet coefficients corresponding to the random noise by using a soft threshold method, and the wavelet coefficients corresponding to the random noise are cleared so that the effect of noise elimination can be realized; and DTCWT inverse algorithm reconstruction is performed on the wavelet coefficients through noise elimination processing so that the denoised intrinsic components are obtained, then adding and reconstruction are performed on the denoised intrinsic components and the residual intrinsic components representing signal useful information and thus the final denoised electroencephalogram signals are obtained. Noise elimination can be realized and the integrity of the useful information can be effectively guaranteed.

Description

technical field [0001] The invention relates to the technical field of electroencephalogram signal denoising, in particular to a method for denoising an electroencephalogram signal. Background technique [0002] Due to the unique complexity and functionality of the brain, humans have always been eager to understand its operating mechanism, so as to protect the brain, treat brain diseases, and even copy the brain to achieve artificial replacement of many functions of the brain. Therefore, to explore the brain and reveal the cognitive mechanism of the brain It is an important and challenging scientific proposition in the process of human beings exploring themselves and understanding nature. [0003] The brain controls and coordinates a series of operations such as language, thinking, cognition, emotion, and movement in human daily life through a large number of nerve cells, and the activity of nerve cells is accompanied by electrical activity. From this, people realized that ...

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Application Information

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IPC IPC(8): G06K9/00
CPCG06F2218/06
Inventor 原博炜郝矿荣
Owner DONGHUA UNIV
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