Researchers at the Institute of IT Security Perform research on Epilepsy Detection with the Aid of Machine Learning
The Department of Computer Science & Security is proud of its successfully completed project on automatic detection of epileptic spikes in long-term EEG monitoring with the aid of machine learning methods.
Oliver Eigner, project leader und researcher, Hubert Schölnast, Junior Researcher at the Institute of IT Security Research and Paul Tavolato, lecturer, determined in partnership with the company Neuro Appliance Technologies whether it is possible to detect areas in EEG recordings which are medically relevant for epilepsy diagnosis in order to support medical staff in analysing long-term EEGs.
The results show that “typical” spikes for epilepsy can be automatically detected and classified with high accuracy in EGG recordings to offer significant support for neurologists. The institute is currently planning a continuation of the project in partnership with the company.