Autosomal Dominant Nocturnal Frontal Lobe Epilepsy Seizure Characterization Through Wavelet Transform Of EEG Records And Self Organizing Maps
Barbara Pisano, Department of Electrical, Electronic Engineering, University of Cagliari
Barbara Cannas, Department of Electrical, Electronic Engineering, University of Cagliari
Giulia Milioli, Sleep Disorder Center, University of Parma
Augusto Montisci, Department of Electrical, Electronic Engineering, University of Cagliari
Fabio Pisano, Department of Electrical, Electronic Engineering, University of Cagliari
Monica Puligheddu, Sleep Disorder Center, University of Cagliari
Giuliana Sias, Department of Electrical, Electronic Engineering, University of Cagliari
Alessandra Fanni, Department of Electrical, Electronic Engineering, University of Cagliari

Abstract:
In this paper, a Manifold Learning approach for the automatic detection of Autosomal Dominant Nocturnal Frontal Lobe Epilepsy seizures is presented, with the aim to support neurologists in the labelling efforts. Features extracted from polysomnographic signals are used in order to detect and discriminate seizure epochs. This task has been addressed by mapping the electroencephalographic signal epochs in different regions of the features space. The result is a Self Organizing Map, which allows to investigate over not straightforward relations in the complex input space for the characterization of seizures.