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Abstract #5414

Multi-scale peak detection method for an automatic cardioballistic artifact period determination directly from EEG-fMRI data

Chung-Ki Wong1, Qingfei Luo1, Vadim Zotev1, Raquel Phillips1, and Jerzy Bodurka1,2,3

1Laureate Institute for Brain Research, Tulsa, OK, United States, 2Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States, 3Center for Biomedical Engineering, University of Oklahoma, Norman, OK, United States

In simultaneous EEG-fMRI, the period of cardioballistic artifact (BCG) in EEG is required for the artifact removal. Recording the electrocardiogram (ECG) waveform during fMRI is difficult, often causing inaccurate period detection. Since the BCG artifact waveform in EEG-fMRI is relatively invariable compared to the ECG waveform, we propose a multiple-scale peak-detection algorithm to determine directly the BCG period from EEG-fMRI data. The algorithm achieves a high detection accuracy of the BCG artifact occurrence on a large EEG-fMRI dataset without using the ECG waveforms, virtually eliminating the need for ECG for BCG artifact removal.

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