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Open AccessJournal ArticleDOI

Seizure prediction: the long and winding road.

Florian Mormann, +3 more
- 01 Feb 2007 - 
- Vol. 130, Iss: 2, pp 314-333
TLDR
A critically discuss the literature on seizure prediction and address some of the problems and pitfalls involved in the designing and testing of seizure-prediction algorithms, and point towards possible future developments and propose methodological guidelines for future studies on seizure predictions.
Abstract
The sudden and apparently unpredictable nature of seizures is one of the most disabling aspects of the disease epilepsy. A method capable of predicting the occurrence of seizures from the electroencephalogram (EEG) of epilepsy patients would open new therapeutic possibilities. Since the 1970s investigations on the predictability of seizures have advanced from preliminary descriptions of seizure precursors to controlled studies applying prediction algorithms to continuous multi-day EEG recordings. While most of the studies published in the 1990s and around the turn of the millennium yielded rather promising results, more recent evaluations could not reproduce these optimistic findings, thus raising a debate about the validity and reliability of previous investigations. In this review, we will critically discuss the literature on seizure prediction and address some of the problems and pitfalls involved in the designing and testing of seizure-prediction algorithms. We will give an account of the current state of this research field, point towards possible future developments and propose methodological guidelines for future studies on seizure prediction.

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Citations
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Journal ArticleDOI

Epileptic Seizure Detection in EEGs Using Time–Frequency Analysis

TL;DR: The suitability of the time-frequency ( t-f) analysis to classify EEG segments for epileptic seizures, and several methods for t- f analysis of EEGs are compared.
Journal ArticleDOI

Single-neuron dynamics in human focal epilepsy

TL;DR: In this paper, the spike train patterns of single neurons during seizures in human epilepsy patients were analyzed and it was found that spiking activity during seizure initiation was highly heterogeneous in small cortical patches and across the network.
Journal ArticleDOI

Automatic seizure detection based on time-frequency analysis and artificial neural networks

TL;DR: A method of analysis of EEG signals, which is based on time-frequency analysis, which provides the final classification of the EEG segments concerning the existence of seizures or not.
References
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Determining Lyapunov exponents from a time series

TL;DR: In this article, the authors present the first algorithms that allow the estimation of non-negative Lyapunov exponents from an experimental time series, which provide a qualitative and quantitative characterization of dynamical behavior.

Theory of communication

Dennis Gabor

Numerical Recipes in FORTRAN - The Art of Scientific Computing - Second Edition

TL;DR: This paper presents a list of recommended recipes for making CDRom decks and some examples of how these recipes can be modified to suit theommelier's needs.
Journal ArticleDOI

Characterization of Strange Attractors

TL;DR: In this article, a measure of strange attractors is introduced which offers a practical algorithm to determine their character from the time series of a single observable, and the relation of this measure to fractal dimension and information-theoretic entropy is discussed.
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