Auto-adaptive Neuromorphic Brain Machine Interface: toward fully embedded neuroprosthetics

Informazioni relative al progetto

NEMO BMI

ID dell’accordo di sovvenzione: 101070891

DOI

10.3030/101070891

Data della firma CE 27 Giugno 2022

Data di avvio 1 Ottobre 2022

Data di completamento 30 Settembre 2026

Finanziato da

• The European Innovation Council (EIC)

Costo totale

€ 2 954 065,88

Contributo UE

€ 2 951 565,88

Coordinato da

COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES
France

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Websites, patent fillings, videos etc. (1)

NEMO BMI website and project logo

NEMO BMI website and project logo including information on social media links

Ethics Requirements (2)

OEI - Requirement No. 4

Second Ethics Advisory Board (EAB) report.

OEI - Requirement No. 3

An independent Ethics Advisory Advisor EAB with expertise in ethics of AI is necessary to advice the applicant on how to address the ethics issues raised by the project First EAB report submission should be done in month 6

Documents, reports (1)

Initial plan for dissemination & exploitation, including communication activities

Initial plan for dissemination exploitation including communication activities

Data Management Plan (1)

NEMO BMI Data Management Plan

Pubblicazioni

Conference proceedings (5)

Grid Search Optimization of Novel SNN-ESN Classifier on a Supercomputer Platform

Autori: Dimitar Penkov, Petia Koprinkova-Hristova, Nikola Kasabov, Simona Nedelcheva, Sofiya Ivanovska & Svetlozar Yordanov
Pubblicato in: Lecture Notes in Computer Science, Numero 13952, 2024, ISSN 1611-3349
Editore: Springer
DOI: 10.1007/978-3-031-56208-2_45

On-line Learning, Classification and Interpretation of Brain Signals using 3D SNN and ESN

Autori: Koprinkova-Hristova, P., Penkov, D., Nedelcheva, S., Yordanov, S., & Kasabov, N.
Pubblicato in: International Joint Conference on Neural Networks (IJCNN), 2023, ISSN 2161-4407
Editore: IEEE
DOI: 10.1109/IJCNN54540.2023.10191974

Hierarchical Hidden Markov Model for Online Decoding in Brain-Computer Interface

Autori: Rémi Souriau, Alexandre Moly, Félix Martel, Lucas Struber, Serpil Karakas, Violaine Juillard, Guillaume Charvet, Tetiana Aksenova
Pubblicato in: 2024 32nd European Signal Processing Conference (EUSIPCO), 2024
Editore: IEEE
DOI: 10.23919/EUSIPCO63174.2024.10715255

Predictors of ECoG-BCI performances across subjects and sessions derived from idle state characteristics

Autori: Lucas Struber, Félix Martel, Serpil Karakas, Violaine Juillard, Angelina Bellicha, Fabien Sauter-Starace, Stéphan Chabardès, Henri Lorach, Guillaume Charvet, Tetiana Aksenova
Pubblicato in: 9th Graz Brain-Computer Interface Conference 2024, 2024, ISBN 978-3-99161-014-4
Editore: Graz University of Technology
DOI: 10.3217/978-3-99161-014-4-015

Auto-adaptation of ECoG-based motor BCI using neural response decoder: a cross-patient study

Autori: Hugo Lafaye de Micheaux, Félix Martel, Fabien Sauter-Starace, Guillaume Charvet, Henri Lorach, Tetiana Aksenova
Pubblicato in: 9th Graz Brain-Computer Interface Conference 2024, 2024, ISBN 978-3-99161-014-4
Editore: Graz University of Technology
DOI: 10.3217/978-3-99161-014-4-013

Peer reviewed articles (1)

Frontiers in Human Neuroscience

Autori: Saad J., Evans A., Jaoui I., Roux-Sibillon V., Hardy E., Anghel L.
Pubblicato in: Frontiers in Human Neuroscience, 2025, ISSN 1662-5161
Editore: Frontiers Research Foundation
DOI: 10.3389/FNHUM.2025.1547074