Statistical Model-Based Classification to Detect Patient-Specific Spike-and-Wave in EEG Signals

Statistical Model-Based Classification to Detect Patient-Specific Spike-and-Wave in EEG Signals

Spike-and-wave discharge (SWD) pattern detection in electroencephalography (EEG) is a crucial signal processing problem in epilepsy applications. It is particularly important for overcoming time-consuming, difficult, and error-prone manual analysis of long-term EEG recordings. This paper presents a...

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Bibliographic Details
Main Authors: Antonio Quintero-Rincón, Valeria Muro, Carlos D’Giano, Jorge Prendes, Hadj Batatia
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Computers
Subjects:
spike-and-wave
generalized Gaussian distribution
EEG
Morlet wavelet
<i>k</i>-nearest neighbors classifier
epilepsy
Online Access:https://www.mdpi.com/2073-431X/9/4/85

Internet

https://www.mdpi.com/2073-431X/9/4/85

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