Objective
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2021-ADG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
70174 Stuttgart
Germany
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