Journal article

EEG datasets for seizure detection and prediction— A review

S Wong, A Simmons, J Rivera-Villicana, S Barnett, S Sivathamboo, P Perucca, Z Ge, P Kwan, L Kuhlmann, R Vasa, K Mouzakis, TJ O'Brien

Epilepsia Open | WILEY | Published : 2023

DOI: 10.1002/epi4.12704

Abstract

Electroencephalogram (EEG) datasets from epilepsy patients have been used to develop seizure detection and prediction algorithms using machine learning (ML) techniques with the aim of implementing the learned model in a device. However, the format and structure of publicly available datasets are different from each other, and there is a lack of guidelines on the use of these datasets. This impacts the generatability, generalizability, and reproducibility of the results and findings produced by the studies. In this narrative review, we compiled and compared the different characteristics of the publicly available EEG datasets that are commonly used to develop seizure detection and prediction a..

View full abstract

Citation metrics

75Scopus
24Web of Science
88Dimensions

Keywords

Data Science
System
Networking and Information Technology R&d (nitrd)
Neurosciences & Neurology
Brain Disorders
Machine Learning
Long-Term
Detection Algorithm
Clinical Neurology
Diagnosis
3209 Neurosciences
Machine Learning and Artificial Intelligence
Neurosciences
Classification
32 Biomedical and Clinical Sciences
Bioengineering
Life Sciences & Biomedicine
Neurodegenerative
Science & Technology
3202 Clinical Sciences