• DocumentCode
    1522491
  • Title

    Modeling of surface myoelectric signals. II. Model-based signal interpretation

  • Author

    Merletti, Roberto ; Roy, Serge H. ; Kupa, Edward ; Roatta, Silvestro ; Granata, Angelo

  • Author_Institution
    Dipt. di Elettronica, Politecnico di Torino, Italy
  • Volume
    46
  • Issue
    7
  • fYear
    1999
  • fDate
    7/1/1999 12:00:00 AM
  • Firstpage
    821
  • Lastpage
    829
  • Abstract
    For pt. I see ibid., vol. 46, no. 7, p. 810-20 (1999). Experimental electromyogram (EMG) data from the human biceps brachii were simulated using the model described in pt. I of this work. A multichannel linear electrode array, spanning the length of the biceps, was used to detect monopolar and bipolar signals, from which double differential signals were computed, during either voluntary or electrically elicited isometric contractions. For relatively low-level voluntary contractions (10%-30% of maximum force) individual firings of three to four-different motor units were identified and their waveforms were closely approximated by the model. Motor unit parameters such as depth, size, fiber orientation and length, location of innervation and tendonous zones, propagation velocity, and source width were estimated using the model. Two applications of the model are described. The first analyzes the effects of electrode rotation with respect to the muscle fiber direction and shows the possibility of conduction velocity (CV) over- and under-estimation. The second focuses on the myoelectric manifestations of fatigue during a sustained electrically elicited contraction and the interrelationship between muscle fiber CV, spectral and amplitude variables, and the length of the depolarization zone. It is concluded that a) surface EMG detection using an electrode array, when combined with a model of signal propagation, provides a useful method for understanding the physiological and anatomical determinants of EMG waveform characteristics and b) the model provides a way for the interpretation of fatigue plots.
  • Keywords
    electromyography; medical signal processing; physiological models; spectral analysis; EMG waveform characteristics; biceps; bipolar signals; depolarization zone length; double differential signals computation; electrical stimulation; electrode rotation effect; fatigue plots interpretation; fiber orientation; model-based signal interpretation; monopolar signals; motor unit parameters; multichannel linear electrode array; muscle fiber direction; propagation velocity; source width; surface myoelectric signals modeling; tendonous zones; Biomedical engineering; Computational modeling; Electrical stimulation; Electrodes; Electromyography; Fatigue; Humans; Muscles; Neuromuscular; Skin; Action Potentials; Electric Stimulation; Electrodes; Electromyography; Evoked Potentials; Humans; Isometric Contraction; Models, Biological; Muscle, Skeletal; Signal Processing, Computer-Assisted;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/10.771191
  • Filename
    771191