Online Symposium: Epileptic Seizure Monitoring: Towards a Wearable Solution

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Epileptic seizure monitoring via wearables is under way. This symposium presents to you the current developments.

About this Event

Worldwide, 65 million people have epilepsy. Despite their medical treatment and follow-up, 35% of patients still suffer from sudden and unforeseen attacks. The biomedical data processing research group of STADIUS (ESAT), KU Leuven, combines their data science expertise with the clinical expertise of UZ Leuven to create a method that detects as accurately as possible when a patient has another epileptic seizure. Using wearables, the monitoring of patients in the home environment is improved and epileptologists can review a part of the recorded data, selected by an automated algorithm.

On 19 April we present to you the state of the art and future perspectives of wearable epileptic seizure monitoring, as well as the lessons learned from the ongoing European SeizelT trials. We finish with the PhD Defense of Kaat Vandecasteele, titled 'Multimodal epileptic seizure detection: towards a wearable solution'.

Within the Flanders AI Research Program, an initiative of the Flemish government, research groups share their AI expertise to jointly tackle challenges of the future. Such groundbreaking AI research to better help patients with epilepsy is one of the pioneer use cases, on which multiple groups in Flanders collaborate. The method presented in this symposium was developed by the biomedical data processing research group, Center for Dynamical Systems, Signal Processing and Data Analytics (STADIUS) at the Department of Electrical Engineering (ESAT) of the KU Leuven, together with UZ Leuven.


  • Sabine Van Huffel, Biomedical Data Processing research group, ESAT-STADIUS, KU Leuven
  • Maarten De Vos, Biomedical Data Processing research group, ESAT-STADIUS, KU Leuven & Department of Development and Regeneration, KU Leuven
  • Borbála Hunyadi, Circuits and Systems Group(CAS), Department of Microelectronics, Delft University of Technology, Delft, the Netherlands
  • Wim Van Paesschen, Laboratory for Epilepsy Research, KU Leuven and Department of Neurology, University Hospitals Leuven

Participation in this event is free, but we do ask to register.

We will distribute the link to the symposium prior to the event via e-mail.


14.30: START Symposium, online link opens

  • 14.50-15.00: introduction by Sabine Van Huffel and Maarten De Vos
  • 15.00-15.30h: Sandor Beniczky - ``Wearable devices for seizure detection: state of the art and future perspectives (see abstract below)
  • 15.30-16.00: Wim Van Paesschen - Wearable devices to detect epileptic seizures: lessons from the SeizeIT trials (see abstract below)
  • 16.00-16.30: Q & A plus discussion with the speakers (moderator: Maarten De Vos)


  • 17.00-19.00: PhD presentation by Kaat Vandecasteele, ``Multimodal epileptic seizure detection: towards a wearable solution, followed by Q & A from the jury
  • 19.00-19.30: PhD ceremony

		Online Symposium: Epileptic Seizure Monitoring: Towards a Wearable Solution image

Epilepsy Monitoring is one of the first use cases developed in the Flanders AI Research Program domain 'Health', supported by the Flemish Government.

		Online Symposium: Epileptic Seizure Monitoring: Towards a Wearable Solution image

Abstract 'Wearable devices for seizure detection: state of the art and future perspectives'

Sandor Beniczky, Head of Clinical Neurophysiology Department, Danish Epilepsy Centre; Professor, Aarhus University, Denmark

A Working Group of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology has recently developed a clinical practice guideline (CPG) to provide recommendations for healthcare personnel working with patients with epilepsy, on the use of wearable devices for automated seizure detection in patients with epilepsy, in outpatient, ambulatory settings. We reviewed the published evidence using The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement and evaluated the evidence and formulated the recommendations following the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. We found high level of evidence for the accuracy of automated detection of generalized tonic-clonic seizures (GTCS) and focal-to-bilateral tonic-clonic seizures (FBTCS) and recommend use of wearable automated seizure detection devices for selected patients when accurate detection of GTCS and FBTCS is recommended as a clinical adjunct. We also found moderate level of evidence for seizure types without GTCs or FBTCs. However, it was uncertain whether the detected alarms resulted in meaningful clinical outcomes for the patients. We recommend using clinically validated devices for automated detection of GTCS and FBTCS, especially in unsupervised patients, where alarms can result in rapid intervention (weak / conditional recommendation). At present, we do not recommend clinical use of the currently available devices for other seizure types (weak / conditional recommendation). Further research and development are needed to improve the performance of automated seizure detection and to document their accuracy and clinical utility.

Abstract 'Wearable devices to detect epileptic seizures: lessons from the SeizeIT trials'

Wim Van Paesschen, Professor in Neurology, UZ Leuven, Leuven, Belgium

The SeizeIT1 trial was an imec-ICON sponsored project which started in 2016 with the aim to develop a multimodal, unobtrusive, wearable seizure detection device. The SeizeIT2 trial is an EIT Health sponsored European study, which started in 2020 to validate a device based on Byteflies Sensor-Dot in typical absences, focal impaired awareness seizures and tonic-clonic seizures. I will discuss issues with respect to hardware and signal quality, biosignals which can be measured (EEG, ECG, EMG, motion, respiration, oxygen saturation, skin temperature), in-hospital versus home-based use, development of algorithms to automatically detect different epileptic seizures, and the full integration of the device into the day-to-day clinical practice of neurologist-epileptologists and electronic health records. We are currently using the wearable as an offline seizure-logging device. In the future, it may be possible to use it as an online, real-time seizure detector-alarming device, and seizure forecaster based on cycles in seizures, sleep, ECG and temperature.

SeizeIT is an Innovation Project of EIT Health, supported by the EIT, a body of the European Union

		Online Symposium: Epileptic Seizure Monitoring: Towards a Wearable Solution image

We thank IEEE / EMB for promoting this event in their extensive network.

		Online Symposium: Epileptic Seizure Monitoring: Towards a Wearable Solution image
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