Performance Metrics for Online Seizure Prediction

Overview

Journal Neural Netw

Specialties Biology
Neurology

Date 2020 May 11

PMID 32387921

Citations 5

Authors

Hsiang-Han Chen

Vladimir Cherkassky

Affiliations

Soon will be listed here.

Abstract

Many recent studies on online seizure prediction from iEEG signal describe various prediction algorithms and their prediction performance. In contrast, this paper focuses on proper specification of system parameters, such as prediction period, prediction horizon and data-driven characterization of lead seizures. Whereas prediction performance clearly depends on these system parameters many researchers simply set the values of these parameters in an ad hoc manner. Our paper investigates the effect of these system parameters on online prediction performance, using both synthetic and real-life data sets. Therefore, meaningful comparison of methods/algorithms (for online seizure prediction) should consider proper specification of system parameters.

Citing Articles

Individualized Seizure Cluster Prediction Using Machine Learning and Chronic Ambulatory Intracranial EEG.

Saboo K, Cao Y, Kremen V, Sladky V, Gregg N, Arnold P IEEE Trans Nanobioscience. 2023; 22(4):818-827.

PMID: 37163411 PMC: 10702269. DOI: 10.1109/TNB.2023.3275037.

The performance evaluation of the state-of-the-art EEG-based seizure prediction models.

Ren Z, Han X, Wang B Front Neurol. 2022; 13:1016224.

PMID: 36504642 PMC: 9732735. DOI: 10.3389/fneur.2022.1016224.

Online Prediction of Lead Seizures from iEEG Data.

Chen H, Shiao H, Cherkassky V Brain Sci. 2021; 11(12).

PMID: 34942859 PMC: 8699082. DOI: 10.3390/brainsci11121554.

Power efficient refined seizure prediction algorithm based on an enhanced benchmarking.

Wang Z, Yang J, Wu H, Zhu J, Sawan M Sci Rep. 2021; 11(1):23498.

PMID: 34873202 PMC: 8648730. DOI: 10.1038/s41598-021-02798-8.

Prediction of Seizure Recurrence. A Note of Caution.

Bosl W, Leviton A, Loddenkemper T Front Neurol. 2021; 12:675728.

PMID: 34054713 PMC: 8155381. DOI: 10.3389/fneur.2021.675728.

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