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A preliminary investigation into the analysis of electromyographic activity using a system of multiple neural networks

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Book cover Artificial Intelligence in Medicine (AIME 1995)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 934))

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Abstract

Electromyography (EMG) is widely used by clinicians and therapists for diagnosis of certain neuromuscular disorders. This paper describes a preliminary examination of the application of multiple neural networks in the analysis of surface electromyographic activity. The multiple neural network system that is currently being developed enables the signal to be actively monitored by tracking changes in clinical assessment indicators such as force levels, dynamic changes in the force and fatigue. The system has been tested on a small number of subjects and shown promising results.

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References

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Authors and Affiliations

  1. Bristol Transputer Centre, UWE, Bristol, UK

    P. Caleb & P. K. Sharpe

  2. MS Research and Resources Unit, Biophysics Group, Bristol Royal Infirmary, UK

    R. Jones

Authors
  1. P. Caleb
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  2. P. K. Sharpe
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  3. R. Jones
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Editor information

Pedro Barahona Mario Stefanelli Jeremy Wyatt

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© 1995 Springer-Verlag Berlin Heidelberg

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Caleb, P., Sharpe, P.K., Jones, R. (1995). A preliminary investigation into the analysis of electromyographic activity using a system of multiple neural networks. In: Barahona, P., Stefanelli, M., Wyatt, J. (eds) Artificial Intelligence in Medicine. AIME 1995. Lecture Notes in Computer Science, vol 934. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60025-6_177

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  • DOI: https://doi.org/10.1007/3-540-60025-6_177

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60025-1

  • Online ISBN: 978-3-540-49407-2

  • eBook Packages: Springer Book Archive

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