Literature DB >> 28920893

A Functional-Genetic Scheme for Seizure Forecasting in Canine Epilepsy.

Elie Bou Assi, Dang K Nguyen, Sandy Rihana, Mohamad Sawan.   

Abstract

OBJECTIVE: The objective of this work is the development of an accurate seizure forecasting algorithm that considers brain's functional connectivity for electrode selection.
METHODS: We start by proposing Kmeans-directed transfer function, an adaptive functional connectivity method intended for seizure onset zone localization in bilateral intracranial EEG recordings. Electrodes identified as seizure activity sources and sinks are then used to implement a seizure-forecasting algorithm on long-term continuous recordings in dogs with naturally-occurring epilepsy. A precision-recall genetic algorithm is proposed for feature selection in line with a probabilistic support vector machine classifier.
RESULTS: Epileptic activity generators were focal in all dogs confirming the diagnosis of focal epilepsy in these animals while sinks spanned both hemispheres in 2 of 3 dogs. Seizure forecasting results show performance improvement compared to previous studies, achieving average sensitivity of 84.82% and time in warning of 0.1.
CONCLUSION: Achieved performances highlight the feasibility of seizure forecasting in canine epilepsy. SIGNIFICANCE: The ability to improve seizure forecasting provides promise for the development of EEG-triggered closed-loop seizure intervention systems for ambulatory implantation in patients with refractory epilepsy.

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Mesh:

Year:  2017        PMID: 28920893     DOI: 10.1109/TBME.2017.2752081

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  3 in total

1.  Epileptic seizure prediction using successive variational mode decomposition and transformers deep learning network.

Authors:  Xiao Wu; Tinglin Zhang; Limei Zhang; Lishan Qiao
Journal:  Front Neurosci       Date:  2022-09-26       Impact factor: 5.152

2.  Bispectrum Features and Multilayer Perceptron Classifier to Enhance Seizure Prediction.

Authors:  Elie Bou Assi; Laura Gagliano; Sandy Rihana; Dang K Nguyen; Mohamad Sawan
Journal:  Sci Rep       Date:  2018-10-19       Impact factor: 4.379

3.  Online Prediction of Lead Seizures from iEEG Data.

Authors:  Hsiang-Han Chen; Han-Tai Shiao; Vladimir Cherkassky
Journal:  Brain Sci       Date:  2021-11-24
  3 in total

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