Investigating the Need for Pediatric-Specific Automatic Seizure Detection

Abstract

Approximately 1 in every 150 children is diagnosed with epilepsy during the first ten years of life [1]. These children experience seizures, which disrupt their lives and directly harm the developing brain. Electroencephalography (EEG) is the main tool used clinically to diagnose seizures and epilepsy. However, the interpretation of EEGs requires time-consuming expert analysis [2]. Automated detection systems are a powerful tool that can help address the issue by reducing expert annotation time. Research on the automatic detection of seizures in pediatric EEG has been limited. Most seizure detection methods have been developed and tested using larger numbers of adult EEG [3], [4]. However, research has shown that brain events in EEG change with ageing [5], [6]. Therefore, model trained on EEGs from adults may not be be suitable for children. To test this hypothesis, we trained a seizure detection model on adult EEG and tested on adult and pediatric EEG recordings.