DBS artifact suppression using a time-frequency domain filter

Electroencephalogram (EEG) is a useful tool for brain research. However, during Deep-Brain Stimulation (DBS), there are large artifacts that obscure the physiological EEG signals. In this paper, we aim at suppressing the DBS artifacts by means of a time-frequency-domain filter. As a pre-processing step, Empirical-Mode Decomposition (EMD) is applied to detrend the raw data. The detrended signals are then filtered iteratively until, by visual inspection, the quality is good enough for interpretation. The proposed algorithm is demonstrated by an application to a clinical DBS-EEG data set in resting state and in finger-tapping condition. Moreover, a comparison with a Low-Pass filter (LPF) is provided, by visual inspection and by a quantitative measure.