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Using in Vivo Subject-Specific Musculotendon Parameters to Investigate Voluntary Movement Changes after Stroke: An EMG-Driven Model of Elbow Joint

Using in Vivo Subject-Specific Musculotendon Parameters to Investigate Voluntary Movement Changes after Stroke: An EMG-Driven Model of Elbow Joint

Hujing Hu, Le Li
Copyright: © 2014 |Pages: 20
ISBN13: 9781466660908|ISBN10: 1466660902|EISBN13: 9781466660915
DOI: 10.4018/978-1-4666-6090-8.ch007
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MLA

Hu, Hujing, and Le Li. "Using in Vivo Subject-Specific Musculotendon Parameters to Investigate Voluntary Movement Changes after Stroke: An EMG-Driven Model of Elbow Joint." Applications, Challenges, and Advancements in Electromyography Signal Processing, edited by Ganesh R. Naik, IGI Global, 2014, pp. 161-180. https://doi.org/10.4018/978-1-4666-6090-8.ch007

APA

Hu, H. & Li, L. (2014). Using in Vivo Subject-Specific Musculotendon Parameters to Investigate Voluntary Movement Changes after Stroke: An EMG-Driven Model of Elbow Joint. In G. Naik (Ed.), Applications, Challenges, and Advancements in Electromyography Signal Processing (pp. 161-180). IGI Global. https://doi.org/10.4018/978-1-4666-6090-8.ch007

Chicago

Hu, Hujing, and Le Li. "Using in Vivo Subject-Specific Musculotendon Parameters to Investigate Voluntary Movement Changes after Stroke: An EMG-Driven Model of Elbow Joint." In Applications, Challenges, and Advancements in Electromyography Signal Processing, edited by Ganesh R. Naik, 161-180. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-6090-8.ch007

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Abstract

Neuromusculoskeletal modeling provides insights into the muscular system which are not always obtained through experiment or observation alone. One of the major challenges in neuromusculoskeletal modeling is to accurately estimate the musculotendon parameters on a subject-specific basis. The latest medical imaging techniques such as ultrasound for the estimation of musculotendon parameters would provide an alternative method to obtain the muscle architecture parameters noninvasively. In this chapter, the feasibility of using ultrasonography to measure the musculotendon parameters of elbow muscles is validated. These parameters help to build a subject-specific EMG-driven model, which could predict the individual muscle force and elbow voluntary movement trajectory using the input of EMG signal without any trajectory fitting procedure involved. The results demonstrate the feasibility of using EMG-driven neuromusculoskeletal modeling with ultrasound-measured data for prediction of voluntary elbow movement for both unimpaired subjects and persons after stroke.

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