During longterm EEG monitoring of epileptic patients, automatic detection methods could be of great assistance because they save a lot of time. The work was develop in cooperation with Micromed Spa with the aim of evaluate and compare the performance of two seizure detection algorithm:one using wavelet based features and one based on AR parameters. The Artificial Neural Network were used as classification method. The results show a better reliability for the ANN having in input AR parameters

Analysis for Automatic Detection of Epileptic Seizure from EEG signals

Pellegrino, Giulia
2014/2015

Abstract

During longterm EEG monitoring of epileptic patients, automatic detection methods could be of great assistance because they save a lot of time. The work was develop in cooperation with Micromed Spa with the aim of evaluate and compare the performance of two seizure detection algorithm:one using wavelet based features and one based on AR parameters. The Artificial Neural Network were used as classification method. The results show a better reliability for the ANN having in input AR parameters
2014-07-14
Seizure Detection Algorithm, Epileptic Seizure, Neural Network, Wavelet, AR model, EEG signal
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/18556