Recognition and removal of EMG artifacts in single-channel EEG signals based on variational mode decomposition and second-order blind identification

Changrui Liu; Chaozhu Zhang

doi:10.1117/12.2643466

9 October 2022 Recognition and removal of EMG artifacts in single-channel EEG signals based on variational mode decomposition and second-order blind identification

Changrui Liu, Chaozhu Zhang

Author Affiliations +

Proceedings Volume 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022); 122460P (2022) https://doi.org/10.1117/12.2643466
Event: 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 2022, Qingdao, China

Abstract

In the process of EEG signal acquisition, it is inevitable to be affected by some artifacts, for the traditional multi-channel EEG signal, researchers have proposed a variety of methods to remove artifacts. However, with the development of wearable EEG acquisition systems, only single-channel EEG signals are collected in many cases. In order to solve the problem that the artifact of single-channel EEG signal is not easy to deal with, this paper proposes an artifact identification and removal method that combines variational mode decomposition (VMD) and second-order blind identification (SOBI). First, the original signal is decomposed into a series of intrinsic modal function (IMF) by the optimized variational modal decomposition. The idea of blind source separation is introduced, and the IMF is used as the input signal of SOBI. Then, the fuzzy entropy and correlation coefficient comprehensive indicators are used to identify extract the components containing artifacts and remove them. Finally, the pure EEG signal is reconstructed by inverse transformation. The semi-simulation experiments show that the proposed method has a better effect of removing EMG artifacts than other existing methods, and can retain useful information to the greatest extent.

Citation Download Citation

Changrui Liu and Chaozhu Zhang "Recognition and removal of EMG artifacts in single-channel EEG signals based on variational mode decomposition and second-order blind identification", Proc. SPIE 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 122460P (9 October 2022); https://doi.org/10.1117/12.2643466

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Electroencephalography

Electromyography

Signal processing

Independent component analysis

Brain

Fuzzy logic

Signal to noise ratio

Show All Keywords

Keywords/Phrases

Search In:

Publication Years