ponencia en congreso.page.titleprefix Epilepsy seizure onset detection applying 1-NN classifier based on statistical parameters
Loading...
Date
2018
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
"Epilepsy is a disease caused by an excessive discharge of a group of neurons in the cerebral cortex.
Extracting this information using EEG signals is an ongoing challenge in biomedical signal processing. In this paper, a new method is proposed for onset seizure detection in epileptic EEG signals based on parameters from the t-location-scale distribution coupled with the variance and the Pearson
correlation coefficient. The 1-nearest neighbor classifier achieved a 91% sensitivity (True positive rate) and 95% specificity (True Negative Rate) with a delay of 4.5 seconds (on average) in the 45 signals analyzed, which suggests that the proposed methodology is potentially useful for seizure
onset detection in epileptic EEG signals."
Description
Keywords
ELECTROENCEFALOGRAFIA, PROCESAMIENTO DE SEÑALES DIGITALES, EPILEPSIA