A Novel Method for ECG Artifact Removal from EEG without Simultaneous ECG.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)(2022)

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摘要
The electrocardiogram (ECG) is a common source of electrical artifact in electroencephalogram (EEG). Here, we present a novel method for removing ECG artifact that requires neither simultaneous ECG nor transformation of the EEG signals. The approach relies upon processing a subset of EEG channels that contain ECG artifact to identify the times of each R-wave of the ECG. Within selected brief epochs, data in each EEG channel is signal-averaged ± 60 ms around each R-wave to derive an ECG template specific to each channel. This template is subtracted from each EEG channel which are aligned with the R-waves. The methodology was developed using two cohorts of infants: one with 128-lead EEG including an ECG reference and another with 32-lead EEG without ECG reference. The results for the first cohort validated the methodology the ECG reference and the second demonstrated its feasibility when ECG was not recorded. This method does not require independent, simultaneous recording of ECG, nor does it involve creation of an artifact template based on a mixture of EEG channel data as required by other methods such as Independent Component Analysis (ICA). Spectral analysis confirms that the method compares favorably to results using simultaneous recordings of ECG. The method removes ECG artifact on an epoch by epoch level and does not require stationarity of the artifact. Clinical Relevance - This approach facilitates the removal of ECG noise in frequency bands known to play a central role in brain mechanisms underlying cognitive processes.
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关键词
Algorithms,Artifacts,Brain,Electrocardiography,Electroencephalography,Humans
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