First Closed-loop non-Invasive Seizure Prevention System (RELIEVE)


This project doesn't include Faculty of Medicine. It includes Central European Institute of Technology. Official project website can be found on
Project Identification
Project Period
4/2023 - 3/2026
Investor / Pogramme / Project type
European Union
MU Faculty or unit
Central European Institute of Technology
Cooperating Organization
Technische Universiteit Delft
Alpha Brain Technologies
IRCCS - Associazione La Nostra Famiglia 'Istituto Scientifico Eugenio Medea'
Stichting Kempenhaeghe
Stichting Epilepsie Instellingen Nederland

Project RELIEVE aims to construct a wearable, seizure predicting and seizure control device for patients with epilepsy. To this end, we will develop hardware and software solutions. The hardware solution comprises three main subsystems. First, a sensor subsystem measures brain signals online via a wearable patch recording the brain electrical activity (EEG). Second, an embedded subsystem that collects and preprocesses other relevant raw physiological data (such as heart rate, eye movements, skin conductance and motion), and implements the software solution for the prediction task. The software solution mainly aims to utilize (possibly by means of development/amendment) an artificial intelligence (AI) approach to detect a measure of seizure onset in brain signals, enabling the control subsystem to act in a timely fashion. In AI terminology, we will develop a classification approach that is robust against variations due to unknown brain dynamics, complicated seizure onset phenomenon, and highly noisy measurements. Once established, this predictive monitoring technology can be integrated with effective interventional approaches such as drug recommendation and neuromodulation to in real-time prevent predicted seizures from happening. The proposed solution aims to be reliable, practical and user-friendly while requiring minimal interactions with experts, representing a smart neuro technology. This technology predicts brain signal anomalies in real time with processing being done on ordinary wearable chipsets without the need to connect or transmit to third party devices or the cloud, guaranteeing system reliability, low battery consumption, and users’ privacy. The proposed solution will deliver a device that potentially pushes the boundary in the field of brain computer interfaces by bringing recent advancements in neurology, signal processing, statistical learning, optimization, and chip technology to the forefront in a unified manner.

Sustainable Development Goals

Masaryk University is committed to the UN Sustainable Development Goals, which aim to improve the conditions and quality of life on our planet by 2030.

Sustainable Development Goal No.  3 – Good health and well-being Sustainable Development Goal No.  9 – Industry, innovation and infrastructure Sustainable Development Goal No.  17 – Partnerships for the goals

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