Skip to primary content

Non-invasive detection, monitoring and prediction of epileptic seizures

Around 0.5% of all adults have active epilepsy. Epileptic seizures are a symptom of a variety of different brain diseases and are associated with substantial a burden for patients, caregivers and communities. Most of the burden relates to persistent seizures despite of modern medical treatment.

Project period

Start: March 2020
End: December 2022

The correct detection, monitoring and prediction of subclinical and subtle epileptic seizures remain a major obstacle for improved seizure control. 


This project aimed at developing new ways of detecting epileptic seizures by analysing involuntary movements of eyes and face. Ongoing studies focus on the feasibility of seizure detection and monitoring using supervised and unsupervised artificial intelligence methods and advanced mathematical analyses based on chaos theory.

The main objective of the project was to develop new applications that allow:

  • detecting ongoing epileptic seizures using common mobile phones.
  • monitoring subclinical epileptic seizures.
  • predicting epileptic seizures by eye tracking glasses.


  • The Mærsk Mc-Kinney Møller Institute, University of Southern Denmark
  • Department of Neurology, Odense University Hospital


  • Odense University Hospital
  • Inge Berthelsen Legat, Danish Epilepsy Association
Christoph Beier

Christoph Beier

Clinical Professor

Odense University Hospital, Department of Neurology

(+45) 6541 1943
Jan Mathias Braun

Jan Mathias Braun

Assistant Professor

University of Southern Denmark, Maersk Mc-Kinney Moller Institute

(+45) 65 50 78 92