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Abstract #4521

Improved cardioballistic artifact waveform for artifact correction with direct cardiac cycle detection from EEG-fMRI data

Chung-Ki Wong1, Qingfei Luo1, Vadim Zotev1, Raquel Phillips1, Kam Wai Clifford Chan2, and Jerzy Bodurka1,3

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

In simultaneous EEG-fMRI, cardioballistic (BCG) artifact removal algorithms require the detection of artifact occurrence time to form subtraction template for artifact correction. The artifact occurrence time can be estimated by an average delay following the R-peak of electrocardiogram (ECG) recording, or directly measured from the BCG component in the EEG data. Here we compared the BCG artifact waveform evaluated by artifact cycles measured from the BCG and ECG data. We found that direct BCG cycle detection from EEG data provides better BCG waveform for the artifact correction and eliminates the need for independent ECG recording.

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