Computational Intelligence Algorithms for Seizure Prediction

Title:

Computational Intelligence Algorithms for Seizure Prediction

Authors:

Bruno Direito [ website | social ]

Ricardo Martins [ website | social ]

Rui Costa [ website | social ]

Antonio Dourado [ website | social ]

Francisco Sales [ website | social ]

Marco Vieira [ website | social ]

Abstract:

Purpose:To develop computational intelligence algorithms for seizure prediction to embed in a transportable device to support refractory epileptic patients.Methods:Firstly a set of features is extracted from the EEG, measuring energy, time-frequency and nonlinear dynamic contents. These features are then used for classification of the brain state into four classes: inter-ictal, pre-ictal, ictal, pos-ictal. Two approaches from computational intelligence are applied: (i) artificial neural networks in the original 14 features space (several architectures are compared: feedforward, with and without memory, radial basis function, Elman), (ii) multidimensional scaling to reduce the 14th dimensional space to 3-dimensional space where classification may be done in an easier way.

Publisher:

8th European Congress on Epileptology, 8th European Congress on Epileptology

Date Published:

2008-09-21

Publisher website:

http://onlinelibrary.wiley.com/doi/10.1111/j.1528-1167.2009.02064.x/abstract

DOI:

10.1111/j.1528-1167.2009.02064.x

Alternative full-text PDF:

download full-text PDF via University of Coimbra

Keywords:

Neural networks, artificial perception, Seizure, epilepsy

Thumbnail:

image

Computational Intelligence Algorithms for Seizure Prediction

Scholarly Lite is a free theme, contributed to the Drupal Community by More than Themes.