Application of the neural network in the study of skeletal muscle with multi-parameters

Jun Shi, Zhuangzhi Yan, Yongping Zheng, Zhang Ha

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


The mechanical properties of skeletal muscles are always related to its architectural changes. But at present, there are very few documents that report the comprehensive study on skeletal muscle with structure morphology, mechanics, electrophysiology and so on. This paper introduced that the muscle thickness and surface electromyography (SEMG) sampled from the extensor carpi radialis by the ultrasound measurement of motion and elasticity system were used to fit the wrist angle with several regression algorithms. The results illuminate that the wrist angle is well fitted by combining the SMG and SEMG signals together, especially with the neural network algorithm, and the results are better than the results fitted by SMG or SEMG alone. So it is better to use multi-parameters to study the skeletal muscle.
Original languageEnglish
Title of host publicationProceedings of the World Congress on Intelligent Control and Automation (WCICA)
Number of pages5
Publication statusPublished - 1 Dec 2006
Event6th World Congress on Intelligent Control and Automation, WCICA 2006 - Dalian, China
Duration: 21 Jun 200623 Jun 2006


Conference6th World Congress on Intelligent Control and Automation, WCICA 2006


  • Neural network
  • Sonomyography
  • Surface electromyography
  • Ultrasound

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Science Applications

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