RodEpil: Laboratory Rodents Dataset for Epileptic Seizure Detection

We introduce a curated video dataset of laboratory
rodents for automatic detection of convulsive events. The dataset
contains short (10 s) top-down and side-view video clips of
individual rodents, labeled at clip level as normal activity or
seizure. It includes 10,101 negative samples and 2,952 positive
samples collected from 19 subjects. We describe the data curation,
annotation protocol and preprocessing pipeline, and report
baseline experiments using a transformer-based video classifier
(TimeSformer). Experiments employ five-fold cross-validation with
strict subject-wise partitioning to prevent data leakage (no subject
appears in more than one fold). Results show that the TimeSformer
architecture enables discrimination between seizure and normal
activity with an average F1-score of 97%. The dataset and baseline
code are publicly released to support reproducible research on non-
invasive, video-based monitoring in preclinical epilepsy research.