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Selective noninvasive electrode to study myoelectric signals

  • Transducers and Electrodes
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Abstract

The paper describes the design and construction of a selective surface electrode for use in a clinical environment. The main criterion of the design was to enable the recognition of individual motor unit action potential trains (MUAPTs) at moderate force levels. The main features of the electrode are, first, a small concentric bipolar arrangement to avoid electrode/muscle fibre alignment problems and to allow measurements within a small, well defined probed volume; secondly, the non-requirements for conducting paste or gel; and thirdly, the casing acting as an earth plate. All of these simplify its use. The results of tests undertaken with the electrode showed that it was able to pick up individual MUAPTs at up to 20 per cent of maximum voluntary contraction from the first dorsal interroseous muscle. Tests were carried out on the small hand muscles to further demonstrate the usefulness of the electrode. A computer program was written to calculate the shift in frequency of the power spectrum of the recorded myoelectric signal with muscle fatigue and hence indirectly to demonstrate the ability of the electrode to detect the reduction in muscle fibre conduction velocity.

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References

  • Agarwal, G. C. andGottlieb (1975) An analysis of the electromyogram by Fourier, simulation and experimental techniques.IEEE Trans.,BME-22, (3), pp. 225–229.

    Google Scholar 

  • Basmajian, J. V. andDeLuca, C. J. (1985)Muscles alive. Williams & Wilkins, 19–222.

  • DeLuca, C. J., Le Fever, R. S. andStulen, F. B. (1979) Pasteless electrode for clinical use.Med. & Biol. Eng. and Comput.,17, 387–390.

    Google Scholar 

  • Jones, N. B. (1981) Some recent advances in electromyography. BioEng. Seminars, Report 81-1, University of California, Berkeley.

    Google Scholar 

  • Jones, N. B., Sehmi, A. S. andLago, P. J. (1987) An emg-force measuring system for assessing muscle condition.Bio-Mechanics in Sport, IMechE, pp. 1–6.

  • Kwatny, E., Thomas, D. H. andKwatny, H. G. (1970) An application of signal processing techniques to the study of myoelectric signals.IEEE Trans.,BME-17, 303–313.

    Google Scholar 

  • Lindstrom, L. (1970) On the frequency spectrum of EMG signals. Ph.D. Thesis, Chalmers University of Technology, Goteborg, Sweden.

    Google Scholar 

  • Loudon, G. H., Jones, N. B. andSehmi, A. S. (1989) Knowledge based decomposition of myoelectric signals. IEE Colloquium on Biomedical Applications of Digital Signal Processing, Conf. Publ. 144, 6/1–6/10.

  • Ludin, H. P. (1980)Electromyography in practice. Georg Theieme Verlag, 48–127.

  • Stulen, F. B. andDeLuca, C. J. (1981) Frequency parameters of the myoelectric signal as a measure of muscle conduction velocity.IEEE Trans.,BME-28, 515–523.

    Google Scholar 

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Bhullar, H.K., Loudon, G.H., Fothergill, J.C. et al. Selective noninvasive electrode to study myoelectric signals. Med. Biol. Eng. Comput. 28, 581–586 (1990). https://doi.org/10.1007/BF02442611

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  • DOI: https://doi.org/10.1007/BF02442611

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