Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
470296 | Computer Methods and Programs in Biomedicine | 2007 | 8 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
V.P. Oikonomou, A.T. Tzallas, D.I. Fotiadis,