NDLI: Elimination of ECG Artifacts from a Single-Channel EEG Using Sparse Derivative Method

Content Provider	IEEE Xplore Digital Library
Author	Kwang Jin Lee Chanki Park Boreom Lee
Copyright Year	2015
Description	Author affiliation: Sch. of Mechatron., Gwangju Inst. of Sci. & Technol. (GIST), Gwangju, South Korea (Chanki Park) \|\| Dept. of Med. Syst. & Eng. (DMSE), Gwangju Inst. of Sci. & Technol. (GIST), Gwangju, South Korea (Kwang Jin Lee; Boreom Lee)
Abstract	The electroencephalogram (EEG) signal has been widely studied in a brain computer interface (BCI) or a polysomnography (PSG) study. However, the EEG can be easily contaminated by electrocardiogram (ECG) artifacts due to high electrical energy of ECG. These artifacts obstruct the analysis of EEG signal. This paper proposes sparse derivative method for eliminating ECG artifacts from a single-channel EEG. In order to evaluate the performance of our proposed method, we compared the proposed method with the combined ensemble empirical mode decomposition and independent component analysis (EEMD+ICA) method by simulation. In addition, we applied the sparse derivative method to real ECG contaminated EEG datasets. Our proposed method could not only estimate and remove ECG artifacts, but also preserve spectral contents of the original EEG. The results of simulation and real data indicate that our proposed method performs better than the EEMD+ICA method.
Starting Page	2384
Ending Page	2389
File Size	516249
Page Count	6
File Format	PDF
e-ISBN	9781479986972
DOI	10.1109/SMC.2015.417
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electrocardiography Electroencephalography Brain modeling Empirical mode decomposition Signal processing algorithms Noise reduction TV artifact removal electroencepahlogram (EEG) electrocardiogram (ECG) artifact sparse derivative ensemble empirical mode decomposition independent component alalysis
Content Type	Text
Resource Type	Article

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