Jelena Skorucak and her team are developing a solution to automate EEG analysis in children with epilepsy. Overnight electroencephalography (EEG) recordings are performed in hospitals in order to diagnose epilepsy, as well as sleep and breathing disorders (e.g., sleep apnoea).
Sleep EEG recordings of young patients (children) can require recording data up to 10 hours, thereby generating large amounts of data for clinicians to process. Standard EEG analysis is a manual process requiring visual inspection of EEG traces in 20 or 30-s segments at a time. This is a cumbersome and time-consuming task for clinicians. Semi-automated methods are urgently sought, where relevant clinical parameters will be automatically calculated and subsequently checked by clinicians.
In her Fellowship, Jelena and her team, are working at the Children’s Hospital Zurich, on automating EEG analysis, with a solution for automated epileptic spike detection, epileptic focus detection, and estimation of sleep recovery parameters. The desired outcome of the project will be an intelligent system solution which can automatically estimate epilepsy and sleep relevant clinical markers.
It will help clinicians in their diagnosis and therapy decisions, resulting in faster and more informative diagnostics procedure. Furthermore, this automated solution can be used in analysis of large-scale data in research or pharma industry which makes data analysis pipelines easier and more standardized.
Affiliation: Prof. Reto Huber
Start date: 04/2023