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Abstract #1405

Improved Spontaneous Activity Maps of Resting Skeletal Musculature by surface EMG-based Contraction Pattern Classification

Martin Schwartz1,2, Günter Steidle1, Petros Martirosian1, Michael Erb3, Bin Yang2, Klaus Scheffler3,4, and Fritz Schick1

1Section on Experimental Radiology, University Hospital of Tübingen, Tübingen, Germany, 2Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany, 3Biomedical Magnetic Resonance, University Hospital of Tübingen, Tübingen, Germany, 4High-Field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany

Reliable assessment and analysis of spontaneous mechanical activities in musculature (SMAM) visible in repetitive DWI is a relatively new technique for non-invasive characterization of skeletal musculature. To correct for data corrupted by intentional contractions, a surface electromyography-based contraction state analysis was investigated to reject undesired DWI data. It is demonstrated that the presented method enables a more reliable quantification of SMAMs and improved spontaneous activity maps.

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