System identification of mechanomyogram evoked by common peroneal nerve stimulation

Tatsuya Higuchi, Takumasa Yamaguchi, Takanori Uchiyama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In the quantitative assessment of a system, a description of the low-order transfer function model is important. The objective of this study was to identify the system of a mechanomyogram (MMG) with SubSpace-based State Space model IDentification (4SID). The input data consisted of the electrical stimulation of the common peroneal nerve, which made the anterior tibial muscle contract. The output data consisted of the evoked MMG. We applied Fourier transform to the MMG signal and obtained a power spectrum. The 10thorder model was estimated by the 4SID method. It was suggested that the frequency band separation of the power spectrum reflected the types of recruited muscle fiber. The results suggest that the MMG is a linear system which can be estimated in the lowerorder transfer function model by applying the 4SID to each frequency band.

Original languageEnglish
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Pages323-325
Number of pages3
Publication statusPublished - 2008
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada
Duration: 2008 Aug 202008 Aug 25

Publication series

NameProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"

Other

Other30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Country/TerritoryCanada
CityVancouver, BC
Period08/8/2008/8/25

Keywords

  • Evoked contraction
  • Mechanomyogram
  • System identification

ASJC Scopus subject areas

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

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