A Kalman filter based methodology for EEG spike enhancement.

Unit of Medical Technology and Intelligent Information Systems, Department of Computer Science, University of Ioannina, GR 45110 Ioannina, Greece.
Computer Methods and Programs in Biomedicine (Impact Factor: 1.56). 03/2007; 85(2):101-8. DOI:10.1016/j.cmpb.2006.10.003
Source: PubMed

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.

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