Simulation-enhanced High-density Magnetomyographic Quantum Sensor Systems for Decoding Neuromuscular Control During Motion

Project Information

qMOTION

Grant agreement ID: 101055186

DOI

10.3030/101055186

EC signature date 31 May 2022

Start date 1 September 2022

End date 31 August 2027

Funded under

• European Research Council (ERC)

Total cost

€ 3 499 763,00

EU contribution

€ 3 499 763,00

Coordinated by

UNIVERSITY OF STUTTGART
Germany

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Other (1)

"Replication Data for: ""High-density magnetomyography is superior to high-density surface electromyography for motor unit decomposition: a simulation study"""

Author(s): Klotz, Thomas and Lehmann, Lena and Negro, Francesco and Röhrle, Oliver
Published in: DaRUS, the data repository of the University of Stuttgart, 2023
Publisher: University of Stuttgart
DOI: 10.18419/darus-3556

Peer reviewed articles (3)

PLoS Computational Biology

Author(s): Laura Schmid; Thomas Klotz; Oliver Röhrle; Randall K. Powers; Francesco Negro; Utku Ş. Yavuz
Published in: PLoS Computational Biology, Vol 20, Iss 1, p e1011487 (2024), 2023, ISSN 1553-734X
Publisher: PLOS Computational Biology
DOI: 10.1101/2023.09.06.556472

Optimizing NV magnetometry for Magnetoneurography and Magnetomyography applications

Author(s): Chen Zhang; Chen Zhang; Jixing Zhang; Matthias Widmann; Magnus Benke; Michael Kübler; Durga Dasari; Thomas Klotz; Leonardo Gizzi; Leonardo Gizzi; Oliver Röhrle; Philipp Brenner; Jörg Wrachtrup
Published in: Frontiers in Neuroscience, Vol 16 (2023), 2023, ISSN 1662-453X
Publisher: Frontiers
DOI: 10.18419/opus-14242

High-density magnetomyography is superior to high-density surface electromyography for motor unit decomposition: a simulation study

Author(s): Thomas Klotz, Lena Lehmann, Francesco Negro, Oliver Röhrle
Published in: Journal of Neural Engineering, Issue 20, 2023, ISSN 1741-2560
Publisher: IOP Publishing
DOI: 10.1088/1741-2552/ace7f7