A Kalman filter based methodology for EEG spike enhancement
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A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
Published on: May 25, 2019
V P Oikonomou1, A T Tzallas, D I Fotiadis
1Unit of Medical Technology and Intelligent Information Systems, Department of Computer Science, University of Ioannina, GR 45110 Ioannina, Greece.
Abstract:
In this work, we present a methodology for spike enhancement in electroencephalographic (EEG) recordings. Our approach takes advantage of the non-stationarity nature of the EEG signal using a time-varying autoregressive model. The time-varying coefficients of autoregressive model are estimated using the Kalman filter. The results show considerable improvement in signal-to-noise ratio and significant reduction of the number of false positives.
