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

Schwartz, M., Steidle, G., Martirosian, P., Erb, M., Yang, B., Scheffler, K., et al. (2018). Improved Spontaneous Activity Maps of Resting Skeletal Musculature by surface EMG-based Contraction Pattern Classification. Poster presented at Joint Annual Meeting ISMRM-ESMRMB 2018, Paris, France.

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Schwartz, M, Author
Steidle, G, Author
Martirosian, P, Author
Erb, M, Author           
Yang, B, Author
Scheffler, K1, 2, Author           
Schick, F, Author
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1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
2Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497796              

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 Abstract: 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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 Dates: 2018-06
 Publication Status: Published in print
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 Identifiers: BibTex Citekey: SchwartzSMEYSS2018
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Title: Joint Annual Meeting ISMRM-ESMRMB 2018
Place of Event: Paris, France
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Title: Joint Annual Meeting ISMRM-ESMRMB 2018
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: 1405 Start / End Page: - Identifier: -