NDLI: Removing cardiac interference from the electroencephalogram using a modified Pan-Tompkins algorithm and linear regression

Content Provider	IEEE Xplore Digital Library
Author	Waser, M. Garn, H.
Copyright Year	2013
Description	Author affiliation: AIT Austrian Inst. of Technol. GmbH, Vienna, Austria (Waser, M.; Garn, H.)
Abstract	Cardiac interference can alter the results of quantitative electroencephalograms (qEEG) used for medical diagnoses. The methods currently employed for the automated removal of cardiac interference, which rely solely on the electroencephalogram (EEG), are susceptible to non-cardiac interference commonly encountered in EEGs. Methods that rely on the electrocardiogram (ECG) - besides being unreliable when non-cardiac artifacts corrupt the ECG - either assume periodicity of the cardiac (QRS) peaks or alter uncorrupted EEG segments. This paper proposes a robust method for the automated removal of cardiac interference from EEGs by identifying QRS peaks in the ECG without assuming periodicity. Artificial signals consisting only of QRS peaks and the zero-lines in between are computed. Linear regression of the EEG channels on the “QRS signals” removes cardiac interference without altering uncorrupted EEG segments. The QRS-based regression method was tested on 30 multi-channel EEGs exhibiting cardiac interference of elderly subjects (15 male, 15 female). Achieving a correction rate of 80%, the QRS-based regression method has proved effective in removing cardiac interference from the EEG even in presence of additional non-cardiac interference in the EEG.
Starting Page	2028
Ending Page	2031
File Size	590000
Page Count	4
File Format	PDF
ISBN	9781457702167
ISSN	1557170X
DOI	10.1109/EMBC.2013.6609929
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-03
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Interference Electrocardiography Filtering Robustness Shape Heart rate
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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