Modeling the relation between muscle thickness and wrist angle based on bone-muscle lever model

Jun Shi, Yongping Zheng, Qinghua Huang, Yisheng Zhu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)

Abstract

Muscle modeling is a powerful tool to study the skeletal muscle, and can give a better perception of the mechanisms of muscular functions. In this study, a mathematical model was proposed based on the bone-muscle lever model to illuminate the non-linear relation between the thickness of extensor carpi radialis muscle and wrist angle. The ultrasound image, SEMG signals were synchronously sampled from the extensor carpi radialis muscle together with the wrist angle during the whole process of wrist extension and flexion to validate the model. The wrist angle was then calculated using the measured muscle thickness by this model. The overall mean correlation coefficient value was 0.96 ± 0.02, and the overall mean standard root mean square error was 5.82 ± 1.95, which were much better than the results of other regression methods. The results show that the wrist angle is well predicted by our model, and it suggests that this model is helpful to study the relationship between internal muscle structural changes and external limb behaviors.
Original languageEnglish
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Pages887-890
Number of pages4
Publication statusPublished - 1 Dec 2008
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada
Duration: 20 Aug 200825 Aug 2008

Conference

Conference30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Country/TerritoryCanada
CityVancouver, BC
Period20/08/0825/08/08

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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