• DocumentCode
    3775410
  • Title

    Assessment muscle fatigue using statistical study and classification: A review

  • Author

    Mohamed Sarillee;M. Hariharan;M.N. Anas;M.I Omar;M.N. Aishah;Q.W. Oung

  • Author_Institution
    Biomedical Electronic Engineering, School of Mechatronic Engineering, Universiti Malaysia Perlis, Campus Pauh Putra, 02600 Arau, Malaysia
  • fYear
    2015
  • Firstpage
    206
  • Lastpage
    211
  • Abstract
    Muscle fatigue is very common muscle condition has been experienced. Different types of myograms have been used to assess muscle fatigue and there are Electromyogram, Mechanomyogram and Acoustic myogram. Each myogram has its own advantages in assessing muscle fatigue. Therefore, suitable features are needed to assess muscle fatigue. This review discusses the on statistical analysis and classification result of the myograms features that have been applied. Towards the end of the paper, challenges and future trends are discussed.
  • Keywords
    "Muscles","Fatigue","Electromyography","Sociology","Statistics","Indexes","Force"
  • Publisher
    ieee
  • Conference_Titel
    Control System, Computing and Engineering (ICCSCE), 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/ICCSCE.2015.7482185
  • Filename
    7482185
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3775410