Mobile EEG-Systems for better epilepsy treatment

Exactly recorded biosignals at the time of the seizure in everyday processes help in the classification of epilepsy disorders, in the optimal dosage of drugs - and perhaps in future even in the development of early warning systems. The project »MOND« contributes to research into these approaches.

MOND - Mobile, smart neurosensing system for the detection and documentation of epileptic seizures in daily life

Detecting and documenting epileptic seizures in daily life is fundamentally important for the individualised treatment of the affected person. Biosignals accurately recorded at the time of the seizure in day-to-day routine help to classify epileptic disorders, optimise drug dosage – or even support the development of early-warning systems. However, recording all the relevant parameters in mobile mode – without significantly restricting the person’s normal routine – presents a tremendous challenge.

The goal of the »MOND« project is to produce proof of concept for an AI-based sensor system for the automatic detection of epileptic seizures in daily life. Data will be recorded via a mobile sensor system worn on the ear, which in particular will make it possible to conduct a mobile electroencephalogram (EEG). An EEG shows the brain’s electrical activity – until now mostly by means of electrodes attached to the scalp.

Alongside developing and testing the system, the project will also explore possible integration in the treatment process. This means that the project partners will not only deal with technical aspects but also with user-friendliness, process reliability and data security as well as use in clinical practice. 

To implement the project successfully, experts in technology development and clinical trials have joined forces, whose expertise has been proven by preliminary work relevant to the project. For example, the »MOND« project builds, among others, on the results of the »EPItect« project (FKZ 16SV7482) funded by the Federal Ministry of Education and Research, which was recently completed and also focussed on a mobile sensor application in the context of epilepsy.

»EPItect« corroborated that the detection of all types of epileptic seizures without recording and analysing EEG signals is insufficient for a clinically significant improvement in the counting of seizures. Consequently, the »MOND« project augments the sensor system with mobile EEG monitoring.

The EEG signal itself and its interpretation are complex. Any movement or the slightest muscle contraction (eye movement, talking, walking) causes massive signal interference or produces false measurement results, known as »artefacts«. The analysis of EEG data recorded by mobile devices represents a particular challenge, which the project will meet with artificial intelligence methods (AI).

Creating new ways to improve the diagnosis and treatment of people with epilepsy – all the partners participating in the »MOND« project are pursuing this common objective, which is to be achieved through the combination of different sensor systems in conjunction with AI methods.

“We’re planning to gather data via a mobile recording unit worn on the ear for EEG and other biosignals. We’ll compare two different EEG systems – one in the ear and the other as a flexible adhesive electrode behind it – in terms of performance and wearing comfort. We hope that especially the EEG data will lead to a clinically significant improvement in the detection of epileptic seizures.«

 

Dr. Insa Wolf
Project Manager and Head of Mobile Neurotechnologies (MNT) at Fraunhofer IDMT

 

Press Release / 15.7.2020

Mobile EEG for the detection of epileptic seizures in daily life

»MOND« project will facilitate better diagnosis and treatment of epilepsy. A mobile neurosensing system suitable for everyday use that detects epileptic seizures automatically and documents them for the purpose of medical anamnesis and optimisation of patient safety.

Project Volume

Total Volume: 3,4 Mio. €
(of which 88 % BMG Funding)

The project is funded by the Federal Ministry of Health BMG as part of the funding priority »Digital innovations for the improvement of patient-centered care in health care, smart sensor technology«.