Advertisement

Medical and Biological Engineering and Computing

, Volume 27, Issue 6, pp 566–571 | Cite as

Median averaging of electromyographic motor unit action potentials: comparison with other techniques

  • S. D. Nandedkar
  • D. B. Sanders
Computing and Data Processing

Abstract

A technique of extracting individual motor unit action potentials (MUAPs) from EMG signals by median averaging, a modification of an existing method, is presented. To compare different techniques of MUAP extraction, 89 MUAPs were recorded with a concentric needle electrode in the brachial biceps muscle of normal subjects and patients with nerve and muscle diseases. MUAPs were also extracted by another method, called split-sweep median averaging, in which alternate MUAP discharges are averaged independently in two computer buffers until the two averaged signals appear equal on visual inspection by the operator. The amplitude, area, area: amplitude ratio, duration and number of phases and turns of each extracted MUAP were determined by each technique. Overall, there was a strong correlation between all features of the MUAPs extracted by median and splitsweep averaging, although the latter method required, on average, twice as many MUAP discharges to produce acceptable signals. We thus conclude that median averaging is a fast and accurate method that requires relatively few MU discharges to extract MUAP signals from spurious background signals.

Keywords

Averaging Computer-aided EMG Motor unit action potentials Template matching 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Andreassen, S. (1987) Methods of computer-aided measurement of motor unit parameters.EEG Suppl.,39, 13–20.Google Scholar
  2. Antoni, L. (1983)AiD: computer programs for automatic EMG analysis. Balinge, Sweden.Google Scholar
  3. Buchthal, F. (1957)An introduction to electromyography. Scandinavian University Books, Copenhagen.Google Scholar
  4. Lowy, K. andWeiss, B. (1968) Assessing the significance of averaged evoked potentials with on-line computer: the split-sweep method.EEG & Clin. Neurophysiol.,25, 177–180.CrossRefGoogle Scholar
  5. Nandedkar, S., Barkhaus, P., Sanders, D. andStålberg, E. (1988) Analysis of amplitude and area of concentric needle EMG motor unit action potentials.,69, 561–567.CrossRefGoogle Scholar
  6. Rosenfalck, P. andRosenfalck, A. (1975) Electromyography and sensory/motor conductions: findings in normal subjects. Laboratory of Clinical Neurophysiology, Rigshospitalet, Copenhagen, 2–4.Google Scholar
  7. Stålberg, E. andAntoni, L. (1983) Computer-aided EMG analysis. InComputer-aided electromyography,Desmedt,J. (Ed.), Karger, Basel, 186–234.Google Scholar
  8. Stålberg, E., Andreassen, S., Falck, B., Lang, H., Rosenfalck, A. andTrojaborg, W. (1986) Quantitative analysis of individual motor unit potentials: a proposition for standardized terminology and criteria for measurement.J. Clin. Neurophysiol.,3, 313–348.Google Scholar
  9. Stewart, C., Nandedkar, S., Massey, J., Gilchrist, J., Barkhaus, P. andSanders, D. (1989) Evaluation of an automatic method of measuring features of motor unit action potentials.Muscle & Nerve,12, 141–148.CrossRefGoogle Scholar

Copyright information

© IFMBE 1989

Authors and Affiliations

  • S. D. Nandedkar
    • 1
  • D. B. Sanders
    • 1
  1. 1.Division of NeurologyDuka University Medical CenterDurhamUSA

Personalised recommendations