Abstract #1405

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

Martin Schwartz^1,2, Günter Steidle¹, Petros Martirosian¹, Michael Erb³, Bin Yang², Klaus Scheffler^3,4, 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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