PREDICTION OF EPILEPSY SEIZURE ONSET USING NONLINEAR ANALYSIS OF EEG RECORDINGS

Grant number: LP0560684 | Funding period: 2006 - 2010

Completed

Abstract

This project will develop the theory and algorithms for reliable and robust prediction of the onset of epileptic seizures and the characterisation of epileptic seizures based on EEG data. Our interdisciplinary team consists of neuroscientists and systems engineers supported with clinicians and software developers. The team will develop the theory and design, implement and evaluate decision support software that is able to interpret eeg data and present epilepsy relevant information to clinicians and patients. Our methods are based on statistical signal processing, nonlinear dynamics (bifurcation and time-series methods) and systems engineering (system identification, adaptive methods).

Related publications (6)

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A data-driven framework for neural field modeling

DR Freestone, P Aram, M Dewar, K Scerri, DB Grayden, V Kadirkamanathan

2011-06-01

This paper presents a framework for creating neural field models from electrophysiological data. The Wilson and Cowan or Amari sty..

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A bifurcation analysis of a modified neural field model: conductance-based synapses act as an anti-epileptic regulatory mechanism

Andre DH Peterson, Iven MY Mareels, Hamish Meffin, David B Grayden, Mark J Cook, Anthony N Burkitt

2011-01-01

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Patient-specific bivariate-synchrony-based seizure prediction for short prediction horizons

Levin Kuhlmann, Dean Freestone, Alan Lai, Anthony N Burkitt, Karen Fuller, David B Grayden, Linda Seiderer, Simon Vogrin, Iven MY Mareels, Mark J Cook

2010-10-01

This paper evaluates the patient-specific seizure prediction performance of pre-ictal changes in bivariate-synchrony between pairs..

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The perturbation response and power spectrum of a mean-field of IF neurons with inhomogeneous inputs

Andre DH Peterson, Hamish Meffin, Anthony N Burkitt, Iven MY Mareels, David B Grayden, Levin Kuhlmann, Mark J Cook

2010-01-01

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Seizure Detection Using Seizure Probability Estimation: Comparison of Features Used to Detect Seizures

Levin Kuhlmann, Anthony N Burkitt, Mark J Cook, Karen Fuller, David B Grayden, Linda Seiderer, Iven MY Mareels

2009-10-01

This paper analyses seizure detection features and their combinations using a probability-based scalp EEG seizure detection framew..

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Analysis of the power spectra, autocorrelation function and EEG time-series signal of a network of leaky integrate-and-fire neurons with conductance-based synapses

Andre DH Peterson, Hamish Meffin, Anthony N Burkitt, Iven MY Mareels, David B Grayden, Levin Kuhlmann, Mark J Cook

2009-09-01