A Comprehensive Machine-Learning-Based Software Pipeline to Classify EEG Signals: A Case Study on PNES vs. Control Subjects

A Comprehensive Machine-Learning-Based Software Pipeline to Classify EEG Signals: A Case Study on PNES vs. Control Subjects

The diagnosis of psychogenic nonepileptic seizures (PNES) by means of electroencephalography (EEG) is not a trivial task during clinical practice for neurologists. No clear PNES electrophysiological biomarker has yet been found, and the only tool available for diagnosis is video EEG monitoring with...

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Bibliographic Details
Main Authors: Giuseppe Varone, Sara Gasparini, Edoardo Ferlazzo, Michele Ascoli, Giovanbattista Gaspare Tripodi, Chiara Zucco, Barbara Calabrese, Mario Cannataro, Umberto Aguglia
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Sensors
Subjects:
eeg
psychogenic nonepileptic seizures
machine learning
Online Access:https://www.mdpi.com/1424-8220/20/4/1235

Internet

https://www.mdpi.com/1424-8220/20/4/1235

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