Obiettivo Non-invasive Brain Machine Interfaces (BMI) bring great promise for neuro-rehabilitation and neuro-prosthesis, as well as for brain control of everyday devices and performance of simple tasks. Over the last 15 years the interest in BMIs has grown substantially, and a variety of interfaces have been developed. The field has been growing dramatically, and market studies reveal an estimated market size of $1.46 billion by 2020. However, non-invasive BMIs have failed to reach the impressive control seen by BMIs implanted in the brain. To date, they require considerable training to reach a moderate level of control, they are susceptible to noise and interference, do not generalize between people and devices, and performance does not show long-term consolidation. Results from our ERC-funded work uncovered a new paradigm that dramatically improves these issues. We propose to develop a prototype for a novel, standalone, non-invasive, noise-resistant BMI, based on an unexplored BMI learning paradigm. In this POC we will 1) refine the brain signal interface (decoder) to be automatically customizable to each individual and produces faster training, 2) implement our BMI technology into a portable hardware-based system, and 3) develop a virtual reality/gaming training platform that will increase learning, performance and consolidation of BMI control. In addition to these technical aims, we propose to explore commercial opportunities and societal benefits, in particular in the health sector. We will conduct market analysis and develop a business case for this product, while expanding industry contacts for production and commercialization.The work proposed in this PoC grant will permit, for the first time to our knowledge, the development of a portable, stand-alone, noise-resistant, and easy to learn BMI, applicable across a wide set of devices, which will bring a significant social impact in health, entertainment and other applications. Campo scientifico natural sciencescomputer and information sciencessoftwaresoftware applicationsvirtual reality Programma(i) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Argomento(i) ERC-PoC-2015 - ERC Proof of Concept Grant Invito a presentare proposte ERC-2015-PoC Vedi altri progetti per questo bando Meccanismo di finanziamento ERC-POC - Proof of Concept Grant Istituzione ospitante FUNDACAO D. ANNA DE SOMMER CHAMPALIMAUD E DR. CARLOS MONTEZ CHAMPALIMAUD Contribution nette de l'UE € 149 625,00 Indirizzo AVENIDA BRASILIA, CENTRO DE INVESTIGACAO DA FUNDACAO CHAMPALIMAUD 1400-038 Lisboa Portogallo Mostra sulla mappa Regione Continente Área Metropolitana de Lisboa Área Metropolitana de Lisboa Tipo di attività Research Organisations Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 149 625,00 Beneficiari (1) Classifica in ordine alfabetico Classifica per Contributo netto dell'UE Espandi tutto Riduci tutto FUNDACAO D. ANNA DE SOMMER CHAMPALIMAUD E DR. CARLOS MONTEZ CHAMPALIMAUD Portogallo Contribution nette de l'UE € 149 625,00 Indirizzo AVENIDA BRASILIA, CENTRO DE INVESTIGACAO DA FUNDACAO CHAMPALIMAUD 1400-038 Lisboa Mostra sulla mappa Regione Continente Área Metropolitana de Lisboa Área Metropolitana de Lisboa Tipo di attività Research Organisations Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 149 625,00