EEG—Single-Channel Envelope Synchronisation and Classification for Seizure Detection and Prediction

This paper tackles the complex issue of detecting and classifying epileptic seizures whilst maintaining the total calculations at a minimum. Where many systems depend on the coupling between multiple sources, leading to hundreds of combinations of electrodes, our method calculates the instantaneous...

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Bibliographic Details
Main Authors: James Brian Romaine, Mario Pereira Martín, José Ramón Salvador Ortiz, José María Manzano Crespo
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Brain Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3425/11/4/516
Description
Summary:This paper tackles the complex issue of detecting and classifying epileptic seizures whilst maintaining the total calculations at a minimum. Where many systems depend on the coupling between multiple sources, leading to hundreds of combinations of electrodes, our method calculates the instantaneous phase between non-identical upper and lower envelopes of a single-electroencephalography channel reducing the workload to the total number of electrode points. From over 600 h of simulations, our method shows a sensitivity and specificity of <inline-formula><math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>100</mn><mo>%</mo></mrow></semantics></math></inline-formula> for high false-positive rates and <inline-formula><math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>83</mn><mo>%</mo></mrow></semantics></math></inline-formula> and <inline-formula><math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>75</mn><mo>%</mo></mrow></semantics></math></inline-formula>, respectively, for moderate to low false positive rates, which compares well to both single- and multi-channel-based methods. Furthermore, pre-ictal variations in synchronisation were detected in over <inline-formula><math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>90</mn><mo>%</mo></mrow></semantics></math></inline-formula> of patients implying a possible prediction system.
ISSN:2076-3425