Hybrid Filter for Removing Power-Supply Artifacts from EEG Signals

Alina Santillán-Guzmán, Ulrich Heute, Ulrich Stephani, Hiltrud Muhle, Andreas Galka, and Michael Siniatchkin


EEG, filtering, powersuppy artifact


Electroencephalographic (EEG) recordings are sometimes contaminated by spurious periodic components picked up from the power-supply equipment. The removal of these components presents a demanding problem because the current techniques do not suppress the artifact efficiently: Either the artifact is only partly eliminated, allowing some residual contribution in the desired signals, or not only the artifact is suppressed but also part of the valuable information. A hybrid filter, which employs both time-domain and frequency-domain representations of the data, is presented here to eliminate only the information considered as spurious. Through an application to real EEG data it is demonstrated that by removing the periodic components directly in time domain and by a subsequent phase and amplitude reconstruction in frequency domain, clean signals are obtained, even if the power of the spurious components is much larger than the power of the true signal. Unlike with most other approaches to filtering, special emphasis is put on optimal phase reconstruction.

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