The relationship between SEMG and change in pennation angle of brachialis

Jun Shi, Yongping Zheng, Zhuangzhi Yan

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

5 Citations (Scopus)

Abstract

Surface Electromyography (SEMG) signals have been widely used for the functional assessment of muscles. On the other hand, sonography has been commonly used to detect the morphological information of human muscles in both static and dynamic conditions. In this study, synchronized ultrasound images and SEMG signals were continuously collected from the brachialis during the process of isometric contraction and subsequent relaxation together with the generated torque measured by a dynamometer. Then the relationships among the root mean square (RMS) of SEMG, the pennation angle, and the torque were investigated. The results of the contraction phase showed an exponential relationship between the RMS and the pennation angle, and a linear relationship between the torque and the pennation angle. The results suggested that SMG together with SEMG may potentially provide a more comprehensive assessment for the muscle functions.
Original languageEnglish
Title of host publication29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
Pages4802-4805
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2007
Event29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07 - Lyon, France
Duration: 23 Aug 200726 Aug 2007

Conference

Conference29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
Country/TerritoryFrance
CityLyon
Period23/08/0726/08/07

ASJC Scopus subject areas

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

Fingerprint

Dive into the research topics of 'The relationship between SEMG and change in pennation angle of brachialis'. Together they form a unique fingerprint.

Cite this