Reporting existing datasets for automatic epilepsy diagnosis and seizure detection
More than 50 million individuals are affected by epilepsy, a chronic
neurological disorder characterized by unprovoked, recurring seizures and
psychological symptoms. Researchers are working to automatically detect or
predict epileptic episodes through Electroencephalography (EEG) signal
analysis, and machine, and deep learning methods. Good quality, open-source,
and free EEG data acts as a catalyst in this ongoing battle to manage this
disease. This article presents 40+ publicly available EEG datasets for adult
and pediatric human populations from 2001-2023. A comparative analysis and
discussion on open and private EEG datasets have been done based on objective
parameters in this domain. Bonn and CHB-MIT remain the benchmark datasets used
for the automatic detection of epileptic and seizure EEG signals. Meta-data has
also been released for large EEG data like CHB-MIT. This article will be
updated every year to report the progress and changing trends in the
development of EEG datasets in this field.