PubMed · 14191714
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R M CHAPMAN. 1964-10-30. ELECTROENCEPHALOGRAPHIC DATA: BASELINE CROSSINGS.. https://doi.org/10.1126/science.146.3644.671
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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.
We reviewed studies on the predictive value of visual evoked potentials (VEPs) in the newborn. VEPs demonstrated a good correlation with neurodevelopmental outcome in full-term infants with birth asphyxia. However, their prognostic value in preterm infants is controversial. In preterm infants, most studies showed high specificities for neurodevelopmental outcome, but some studies demonstrated lower sensitivities.