A Preliminary Study of Muscular Artifact Cancellation in Single-Channel EEG

Sensors

Xun Chen¹  Aiping Liu²  Hu Peng¹ 

[1] Department of Biomedical Engineering, School of Medical Engineering, Hefei University of Technology, Hefei 230009, China; E-Mail:;Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; E-Mails:

关键词: EEG;    single-channel;    muscular artifacts;    EEMD;    JBSS;   

DOI  :  10.3390/s141018370

来源: mdpi

【 摘 要 】

Electroencephalogram (EEG) recordings are often contaminated with muscular artifacts that strongly obscure the EEG signals and complicates their analysis. For the conventional case, where the EEG recordings are obtained simultaneously over many EEG channels, there exists a considerable range of methods for removing muscular artifacts. In recent years, there has been an increasing trend to use EEG information in ambulatory healthcare and related physiological signal monitoring systems. For practical reasons, a single EEG channel system must be used in these situations. Unfortunately, there exist few studies for muscular artifact cancellation in single-channel EEG recordings. To address this issue, in this preliminary study, we propose a simple, yet effective, method to achieve the muscular artifact cancellation for the single-channel EEG case. This method is a combination of the ensemble empirical mode decomposition (EEMD) and the joint blind source separation (JBSS) techniques. We also conduct a study that compares and investigates all possible single-channel solutions and demonstrate the performance of these methods using numerical simulations and real-life applications. The proposed method is shown to significantly outperform all other methods. It can successfully remove muscular artifacts without altering the underlying EEG activity. It is thus a promising tool for use in ambulatory healthcare systems.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.