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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
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Author(s): Hujing Hu (First Affiliated Hospital, Sun Yat-sen University, China & Guangdong Provincial Work Injury Rehabilitation Center, China)and Le Li (First Affiliated Hospital, Sun Yat-sen University, China)
Copyright: 2014
Pages: 20
Source title:
Applications, Challenges, and Advancements in Electromyography Signal Processing
Source Author(s)/Editor(s): Ganesh R. Naik (University of Technology Sydney (UTS), Australia)
DOI: 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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