Objectif Being able to decode neural signals that control skeletal muscles with high accuracy will enable scientific breakthroughs in diagnostics and treatment, including early detection of neurodegenerative diseases, optimising personalised treatment or gene therapy, and assistive technologies like neuroprostheses. This breakthrough will require technology that is able to record signals from skeletal muscles in sufficient detail to allow the morpho-functional state of the neuromuscular system to be extracted. No existing technology can do this. Measuring the magnetic field induced by the flow of electrical charges in skeletal muscles, known as Magnetomyography (MMG), is expected to be the game-changing technology because magnetic fields are not attenuated by biological tissue. However, the extremely small magnetic fields involved require extremely sensitive magnetometers. The only promising option is novel quantum sensors, such as optically pumped magnetometers (OPMs), because they are small, modular, and can operate outside of specialised rooms. Our vision is to use this technology and our expertise in computational neuromechanics to decode, for the first time, neuromuscular control of skeletal muscles based on in vivo, high-density MMG data. For this purpose, we will design the first high-density MMG prototypes with up to 96 OPMs and develop custom calibration techniques. We will record magnetic fields induced by contracting skeletal muscles at the highest resolution ever measured. Such data, combined with the advanced computational musculoskeletal system models, will allow us to derive robust and reliable source localisation and separation algorithms. This will provide us with unique input for subject-specific neuromuscular models. We will demonstrate the superiority of the data over existing techniques with two applications; signs of ageing and neuromuscular disorders and show that it is possible to transfer these methodologies to clinical applications. Champ scientifique sciences médicales et de la santébiotechnologie médicalegénie génétiquethérapie géniqueingénierie et technologiegénie électrique, génie électronique, génie de l’informationingénierie électroniquecapteurssciences naturellesinformatique et science de l'informationlogiciellogiciel d’applicationlogiciel de simulation Programme(s) HORIZON.1.1 - European Research Council (ERC) Main Programme Thème(s) ERC-2021-ADG - ERC ADVANCED GRANTS Appel à propositions ERC-2021-ADG Voir d’autres projets de cet appel Régime de financement ERC - Support for frontier research (ERC) Coordinateur UNIVERSITY OF STUTTGART Contribution nette de l'UE € 3 499 763,00 Adresse Keplerstrasse 7 70174 Stuttgart Allemagne Voir sur la carte Région Baden-Württemberg Stuttgart Stuttgart, Stadtkreis Type d’activité Higher or Secondary Education Establishments Liens Contacter l’organisation Opens in new window Site web Opens in new window Participation aux programmes de R&I de l'UE Opens in new window Réseau de collaboration HORIZON Opens in new window Autres sources de financement € 0,00
