Transcutaneous Muscle Stimulation

  • James D. Sweeney

The high-voltage, brief pulse width stimulus train applied by the latest generations of conducted electrical weapons (CEWs), such as the TASER® M26 and X26 CEWs, are intended primarily to strongly activate skeletal muscle contraction (thus disabling the target individual through incapacitation of their ability to move and to stand), while secondarily also eliciting strong sensations of pain and/or exhaustion. TASER CEW stimuli applied through transcutaneous darts which have contacted or penetrated the surface of the torso are inherently protective against cardiac events because current needs to penetrate deep within the torso to reach the heart itself, and because stimulus pulse widths needed to activate the heart are longer in duration than those needed to stimulate skeletal muscle or nerve.


Motor Unit Skeletal Muscle Contraction Rectangular Stimulus High Frequency Electrical Stimulation Extensor Digitorum Communis Muscle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Lake, D.A., Neuromuscular electrical stimulation. An overview and its application in the treatment of sports injuries. Sports Med, 1992. 13(5): pp. 320–36.PubMedCrossRefGoogle Scholar
  2. 2.
    Rushton, D.N., Electrical stimulation in the treatment of pain. Disability & Rehabilitation, 2002. 24(8): pp. 407–15.CrossRefGoogle Scholar
  3. 3.
    Rattay, F., Analysis of models for extracellular fiber stimulation. IEEE Trans Biomed Eng, 1989. 36(7): pp. 676–82.PubMedCrossRefGoogle Scholar
  4. 4.
    Reilly, J.P., Applied bioelectricity: from electrical stimulation to electrical pathology. 1998, New York: Springer. 1–563.Google Scholar
  5. 5.
    Weiss, G., Sur la possibilite' de rendre comparable entre eux les appareils survant a l'excitation electrique. Arch Ital de Biol, 1901. 35: pp. 413–46.Google Scholar
  6. 6.
    Li, C.L. and A. Bak, Excitability characteristics of the A- and C-fibers in a peripheral nerve. Exp Neurol, 1976. 50(1): pp. 67–79.PubMedCrossRefGoogle Scholar
  7. 7.
    Koslow, M., A. Bak, and C.L. Li, C-fiber excitability in the cat. Exp Neurol, 1973. 41(3): pp. 745–53.PubMedCrossRefGoogle Scholar
  8. 8.
    McIntyre, C.C., A.G. Richardson, and W.M. Grill, Modeling the excitability of mammalian nerve fibers: influence of afterpotentials on the recovery cycle. J Neurophysiol, 2002. 87(2): pp. 995–1006.PubMedGoogle Scholar
  9. 9.
    Carnevale, N.T. and M.L. Hines, The NEURON book. 2006, Cambridge; New York: Cambridge University Press. xix, 457p.CrossRefGoogle Scholar
  10. 10.
    Monti, R.J., R.R. Roy, and V.R. Edgerton, Role of motor unit structure in defining function. Muscle & Nerve, 2001. 24(7): pp. 848–66.CrossRefGoogle Scholar
  11. 11.
    Burke, R.E., Firing patterns of gastrocnemius motor units in the decerebrate cat. J Physiol, 1968. 196(3): pp. 631–54.PubMedGoogle Scholar
  12. 12.
    McPhedran, A.M., R.B. Wuerker, and E. Henneman, Properties of motor units in a heterogeneous pale muscle (M. Gastrocnemius) of the cat. J Neurophysiol, 1965. 28: pp. 85–99.PubMedGoogle Scholar
  13. 13.
    Johnson, M.A., J. Polfar, D. Weightman, and D. Appleton, Data on the distribution of fibre types in thirty-six human muscles. An autopsy study. J Neurol Sci, 1973. 18(1): pp. 111–29.PubMedCrossRefGoogle Scholar
  14. 14.
    Enoka, R.M., Morphological features and activation patterns of motor units. J Clin Neurophysiol, 1995. 12(6): pp. 538–59.PubMedCrossRefGoogle Scholar
  15. 15.
    Monster, A.W. and H. Chan, Isometric force production by motor units of extensor digitorum communis muscle in man. J Neurophysiol, 1977. 40(6): pp. 1432–43.PubMedGoogle Scholar
  16. 16.
    Ding, J., A.S. Wexler, and S.A. Binder-Macleod, A mathematical model that predicts the force-frequency relationship of human skeletal muscle. Muscle Nerve, 2002. 26(4): pp. 477–85.PubMedCrossRefGoogle Scholar
  17. 17.
    Ding, J., A.S. Wexler, and S.A. Binder-Macleod, A predictive fatigue model-I: Predicting the effect of stimulation frequency and pattern on fatigue. IEEE Trans Neural Syst Rehabil Eng, 2002. 10(1): pp. 48–58.PubMedCrossRefGoogle Scholar
  18. 18.
    Ding, J., A.S. Wexler, and S.A. Binder-Macleod, Development of a mathematical model that predicts optimal muscle activation patterns by using brief trains. J Appl Physiol, 2000. 88(3): pp. 917–25.PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of BioengineeringFlorida Gulf Coast UniversityFlorida

Personalised recommendations