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

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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 EMGdriven neuromusculoskeletal modeling with ultrasound-measured data for prediction of voluntary elbow movement for both unimpaired subjects and persons after stroke.

Original languageEnglish
Title of host publicationApplications, Challenges, and Advancements in Electromyography Signal Processing
PublisherIGI Global
Pages161-180
Number of pages20
ISBN (Electronic)9781466660915
ISBN (Print)1466660902, 9781466660908
DOIs
StatePublished - 31 May 2014
Externally publishedYes

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