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Improved algorithm for ballistocardiac artifact removal from EEG simultaneously recorded with fMRI

The simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance image (fMRI) is a promising tool that is capable of providing high spatiotemporal brain mapping. One of the difficulties to obtain high-quality simultaneous EEG/fMRI data comes from the heartbeat artifact induced in the EEG recorded within fMRI scanner. The purpose of this study was to develop a novel algorithm for removing heartbeat artifact, thus overcoming problems associated with previous methods. Our method consists of a mean artifact waveform subtraction, the selective removal of wavelet coefficients, and a recursive least-square adaptive filtering. The recursive least square adaptive filtering operates without dedicated sensor for the reference signal, and only when the mean subtraction and wavelet-based noise removal is not satisfactory. The performance of our system has been assessed using simulated data based on experimental data of various spectral characteristics, and actual experimental data of alpha-wave-dominant normal EEG and epileptic EEG.