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Updated: Jan 13, 2026

Inducing Post-Traumatic Epilepsy in a Mouse Model of Repetitive Diffuse Traumatic Brain Injury
Published on: February 10, 2020
Automated video-based differentiation of sleep-related hypermotor epilepsy and parasomnia episodes
Matteo Moro1,2, Federica Sassi3, Ramona Cordani4,5
1Department of Informatics, Bioengineering, Robotics and Systems Engineering (DIBRIS), University of Genova, Genova, Italy. matteo.moro@unige.it.
Abstract:
Distinguishing epileptic seizures from parasomnias is challenging due to overlapping motor features. This study evaluated a SlowFast deep learning model using video recordings of 167 individuals to classify Sleep-Related Hypermotor Epilepsy, Disorders of Arousal, and REM Sleep Behavior Disorder. The model achieved a mean accuracy of 83.3% across three data splits. This work represents an initial step toward developing automated tools to support clinicians in assessing sleep-related motor events.
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