
University of Stuttgart
University of Stuttgart
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548 Projects, page 1 of 110
Open Access Mandate for Publications and Research data assignment_turned_in Project2022 - 2027Partners:University of StuttgartUniversity of StuttgartFunder: European Commission Project Code: 101055186Overall Budget: 3,499,760 EURFunder Contribution: 3,499,760 EURBeing 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.
more_vert assignment_turned_in Project2008 - 2012Partners:CEA, BBT, INCDE ICEMENERG, University of Manchester, KGHM Cuprum (Poland) +32 partnersCEA,BBT,INCDE ICEMENERG,University of Manchester,KGHM Cuprum (Poland),CKTI,Disaster Management Directorate of Tolna County,General Electric (France),Technische Universität Braunschweig,RWE,DR WILLIGE Barbara Katharina,JRC,EOAE,DOW Deutschland,Goa University,University of Stuttgart,WOELFEL BERATENDE INGENIEURE GMBH &CO KG,kznpp,FHG,ČVUT,INSTITUTE OF MECHANICS, CHINESE ACADEMY OF SCIENCES,Luleå University of Technology,BAM,MEGA Risk,VRVis (Austria),University of Sheffield,POLITO,INRIA,Aristotle University of Thessaloniki,ERF GMBH,UPCT,TU Delft,DAE,VCE,APLICA,RISKENG,MUGFunder: European Commission Project Code: 213968more_vert - CNRS,TUM,UCD,CEA,LG,EPFZ,KIT,SNS,UNIBAS,IPHT,UPV/EHU,University of Stuttgart,Chalmers University of Technology,UC,TU DelftFunder: European Commission Project Code: 248629
more_vert assignment_turned_in Project2012 - 2016Partners:SISMEL, University of Cassino and Southern Lazio, CERL, FU, University of Birmingham +11 partnersSISMEL,University of Cassino and Southern Lazio,CERL,FU,University of Birmingham,National Library of the Czech Republic,KB,FEF,UGOE,EUROCEAN,KCL,University of Stuttgart,MATHEMATICAL INSTITUTE OF THE SERBIAN A,INRIA,Trinity College Dublin, Ireland,SASAFunder: European Commission Project Code: 284432more_vert Open Access Mandate for Publications and Research data assignment_turned_in Project2019 - 2023Partners:UC, Carlos III University of Madrid, Silesian University of Technology, BALIKESIR ELECTROMECHANICAL INDUSTRIAL PLANTS INC., Sapienza University of Rome +4 partnersUC,Carlos III University of Madrid,Silesian University of Technology,BALIKESIR ELECTROMECHANICAL INDUSTRIAL PLANTS INC.,Sapienza University of Rome,University of Manchester,University of Stuttgart,SEA MARCONI TECHNOLOGIES DI VANDERTUMIATTI SAS,University of ExeterFunder: European Commission Project Code: 823969Overall Budget: 685,400 EURFunder Contribution: 685,400 EURThe BIOTRAFO project will analyze the effect of temperature on the designs of power transformers that use biodegradable esters as coolant, the environmental and fire performance of these liquids will be also evaluated. These machines are very common in our power distribution systems. Since electricity is generated until it reaches households, it passes through an average of four transformers. Currently the liquid used in most of these machines is a petroleum derivative, since its good performance is well known. However, the environmental awareness of many companies is demanding new transformers that are cooled by esters of natural origin. In this framework, BIOTRAFO proposes a study that allows to know the temperature in the windings of the transformer when using biodegradable liquids, which by their nature are more viscous. This temperature is a critical factor for the useful life of the transformer, due to the aging of dielectric solid materials. The aging of these materials when immersed in these liquids will also be analyzed. Not only the question will be observed from a theoretical perspective, industrial platforms will also be used to test the generated models. The results of the research will be disseminated among specialized and non-specialized audiences, considering the commercial exploitation of the results obtained. The project will also carry out tasks of knowledge transfer generated for this purpose, the training aspects of the research personnel involved in the project will be taken care of.Finally, the management and coordination of the project will be efficiently organized. To carry out this task, a consortium of thirteen partners has been formed, six of which do not belong to the EU. All of them have knowledge and proven experience in the field of study. Ten of the partners belong to the academic sector and three are companies. Two are manufacturers of power transformers, while the other performs diagnostic work on transformers that are in operation
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