• DocumentCode
    2281666
  • Title

    Muscle fatigue analysis in young adults at different MVC levels using EMG metrics

  • Author

    Zaman, Abdullah Al ; Sharmin, Tanzia ; Khan, Mohammad Ashraf Ali ; Ferdjallah, Mohammed

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Tennessee Univ., Knoxville, TN
  • fYear
    2007
  • fDate
    22-25 March 2007
  • Firstpage
    390
  • Lastpage
    394
  • Abstract
    Spectral parameters such as the mean and median frequencies have been documented to be reliable outcome variables for the assessment of muscle fatigue. The objective of this paper is to examine young subjects´ surface electromyography (EMG) signals at different levels of maximum voluntary contractions (MVC) and to analyze spectral shifts in mean and median frequencies (MNF, MDF). In this study, continuous stream of EMG data sets from lower extremity muscles are used to characterize muscular fatigue from minimum to maximum MVC level. EMG data were recorded from the biceps brachii muscles during isometric contraction at constant torque levels using automated dynamometer. EMG metrics such as MNF, MDF, root mean square (RMS), and rectified root mean square (RRMS) were computed to assess muscle fatigue patterns.
  • Keywords
    electromyography; fatigue; neuromuscular stimulation; EMG data sets; EMG metrics; automated dynamometer; biceps brachii muscles; constant torque levels; different MVC levels; isometric contraction; lower extremity muscles; muscle fatigue analysis; rectified root mean square; spectral parameters; surface electromyography signals; voluntary contractions; young adults; Electrodes; Electromyography; Fatigue; Frequency; Muscles; Neurons; Pain; Recruitment; Root mean square; Signal generators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SoutheastCon, 2007. Proceedings. IEEE
  • Conference_Location
    Richmond, VA
  • Print_ISBN
    1-4244-1028-2
  • Electronic_ISBN
    1-4244-1029-0
  • Type

    conf

  • DOI
    10.1109/SECON.2007.342930
  • Filename
    4147460