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Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
Published on: July 26, 2013
Ballistocardiogram artifact removal from EEG signals using adaptive filtering of EOG signals
Myung H In1, Soo Y Lee, Tae S Park
1Department of Biomedical Engineering, Kyung Hee University, 1 Seochun, Kiheung, Yongin, Kyungki 446-701, Korea.
Abstract:
We estimated ballistocardiogram (BCG) components in EEG signals recorded inside an MRI magnet using the electro-oculogram (EOG) signals recorded simultaneously with the EEG signals. Since the EOG signals are measured near the EEG measuring points, it is thought that the BCG components in the EOG signals resemble the BCG components in the EEG signals. To estimate the BCG components in the EEG signals, we applied the Kalman filter to the EOG and EEG signals recorded inside a 3.0 T MRI magnet. After removing the estimated BCG components from the EEG signals, we extracted the visual-evoked potentials (VEPs) from the BCG-removed EEG signals. To validate the efficacy of Kalman filtering in the BCG artifact removal, we have compared three types of VEPs of eight healthy subjects: one extracted from the raw EEG signals measured outside the magnet and the others extracted from the BCG-removed EEG signals measured inside the magnet. The BCG artifacts have been removed with Kalman filtering as well as with the conventional BCG template subtraction method for the sake of comparison. No significant difference in waveforms, latencies and amplitudes has been found between the two types of VEPs extracted from the two kinds of BCG-removed EEG signals.

