ORCID Profile
0000-0001-8402-2853
Current Organisation
Deakin University
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Publisher: ACM Press
Date: 2016
Publisher: Wiley
Date: 16-02-2023
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 algorithms. We investigated the advantages and limitations of the characteristics of the EEG datasets. Based on our study, we identified 17 characteristics that make the EEG datasets unique from each other. We also briefly looked into how certain characteristics of the publicly available datasets affect the performance and outcome of a study, as well as the influences it has on the choice of ML techniques and preprocessing steps required to develop seizure detection and prediction algorithms. In conclusion, this study provides a guideline on the choice of publicly available EEG datasets to both clinicians and scientists working to develop a reproducible, generalizable, and effective seizure detection and prediction algorithm.
Publisher: ACM
Date: 07-11-2017
Publisher: Elsevier BV
Date: 06-2020
Publisher: Springer International Publishing
Date: 2021
Publisher: ACM
Date: 05-10-2020
Publisher: IEEE
Date: 09-2021
Publisher: ACM
Date: 16-10-2020
Publisher: IEEE
Date: 05-2022
Publisher: IEEE
Date: 08-2020
Publisher: MDPI AG
Date: 10-10-2023
DOI: 10.3390/S23208375
Publisher: ACM
Date: 27-06-2020
Publisher: Auerbach Publications
Date: 05-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: SCITEPRESS - Science and Technology Publications
Date: 2020
No related grants have been discovered for Angie Simmons.