Noninvasive imaging of internal muscle activities from multi-channel surface EMG recordings

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

3 Scopus citations

Abstract

Surface Electromyogram (sEMG) technology provides a non-invasive way for rapid monitoring muscle activities, but its poor spatial resolution and specificity limit its application in clinic. To overcome these limitations, a noninvasive muscle activity imaging (MAI) approach has been developed and used to reconstruct internal muscle activities from multi-channel sEMG recordings. A realistic geometric hand model is developed from high-resolution MR images and a distributed bioelectric dipole source model is employed to describe the internal muscle activity space of the muscles. The finite element method and weighted minimum norm method are utilized solve the forward and inverse problems respectively involved in the proposed MAI technique. A series of computer simulations was conducted to test the performance of the proposed MAI approach. Results show that reconstruction results achieved by the MAI technique indeed provide us more detailed and dynamic information of internal muscle activities, which enhance our understanding of the mechanisms underlying the surface EMG recordings.

Original languageEnglish (US)
Title of host publication2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
Pages5430-5432
Number of pages3
DOIs
StatePublished - Oct 31 2013
Event2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 - Osaka, Japan
Duration: Jul 3 2013Jul 7 2013

Other

Other2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
CountryJapan
CityOsaka
Period7/3/137/7/13

ASJC Scopus subject areas

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

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