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RELIEVE

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First Closed-loop non-Invasive Seizure Prevention System

The goal of Project RELIEVE is to build the very first non-invasive effective closed-loop monitoring and intervention system for brain-related disorders. The outcomes can be used to treat or manage various psychiatric and neurolog... ver más

31/03/2026

3M€

Presupuesto del proyecto: 3M€

Líder del proyecto

Masarykova univerzita No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2023-04-01

HORIZON-EIC-2022-PATHFINDEROPEN-01-01: EIC Pathfinder Open 2022 Scope:You should apply to this call if you are looking for support from EIC Pathfinder Open to reali...

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Duración del proyecto: 35 meses Fecha Inicio: 2023-04-01
Fecha Fin: 2026-03-31

Líder del proyecto

Masarykova univerzita No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 3M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The goal of Project RELIEVE is to build the very first non-invasive effective closed-loop monitoring and intervention system for brain-related disorders. The outcomes can be used to treat or manage various psychiatric and neurological disorders. We do this by pushing the technological boundaries in two separate domains. (1) AI domain: We develop a class of mathematical and algorithmic tools for brain data based on the recently developed mathematical theories that are potentially useful for the real-time monitoring of the brain data. Such advancements have shown promise in robotics and self-driving cars and have high potential to work efficiently in highly dynamic environments where personalization and low computation power is a must. This makes such algorithms runnable using brain data such as EEG (electric activity on the head surface) on ordinary wearable devices. (2) Neurostimulation domain: We combine two characteristics of the ultrasound waves in stimulation and imaging of the nervous system to build the first smart-navigated wearable ultrasound patch. We also choose the vagus nerve as the target for neurostimulation as one of the most promising sites to interact with the nervous system with proven implications for a large spectrum of neurological and psychiatric disorders (e.g. dementia, depression, epilepsy, etc.). We call this unit 'WU-VNS' standing for non-invasive wearable ultrasound vagus nerve stimulation.In the next three years, we will use epilepsy as the first use case of the developed technologies to train and test a closed-loop system. For this, the AI monitors the brain through a patch that records EEG in addition to other physiological measures such as heart rate and motion. Upon prediction of a forthcoming anomaly (seizure in this case) by the AI unit, the neurostimulation module activates and stimulates the vagus nerve non-invasively. During this process also a so-called 'active learning' happens in which the AI learns from the reactions of the nervous system to the stimulation protocol and can fine-tune the protocol for future interventions.To achieve this, we have designed a complex phase-based development and testing plan: The first two generations (Gen. 1 and 2) are the intermediate versions of the full system and act in open loops validating each of the AI and neurostimulation subsystems. These two generations already have high potentials to independently turn into medical device products with large market needs. Ultimately, in Gen. 3 we close the loop by integrating the AI and the WU-VNS and consequently validate the efficacy and the usability of the system.

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