Skip to main content
Log in

Methods for estimating muscle fibre conduction velocity from surface electromyographic signals

  • Review
  • Published:
Medical and Biological Engineering and Computing Aims and scope Submit manuscript

Abstract

The review focuses on the methods currently available for estimating muscle fibre conduction velocity (CV) from surface electromyographic (EMG) signals. The basic concepts behind the issue of estimating CV from EMG signals are discussed. As the action potentials detected at the skin surface along the muscle fibres are, in practice, not equal in shape, the estimation of the delay of propagation (and thus of CV) is not a trivial task. Indeed, a strictly unique definition of delay does not apply in these cases. Methods for estimating CV can thus be seen as corresponding to specific definitions of the delay of propagation between signals of unequal shape. The most commonly used methods for CV estimation are then reviewed. Together with classic methods, recent approaches are presented. The techniques are described with common notations to underline their relationships and to highlight when an approach is a generalisation of a previous one or when it is based on new concepts. The review identifies the difficulties of CV estimation and underlines the issues that should be considered by the investigator when selecting a particular method and detection system for assessing muscle fibre CV. The many open issues in CV estimation are also presented.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Arendt-Nielsen, L., andMills, K. R. (1985): ‘The relationship between mean power frequency of the EMG spectrum and muscle fibre conduction velocity’,Electroencephalogr: Clin. Neurophysiol.,60, pp. 130–134

    Article  Google Scholar 

  • Arendt-Nielsen, L., andZwarts, M. (1989): ‘Measurement of muscle fibre conduction velocity in humans: techniques and applications’,J. Clin. Neurophysiol.,6, pp. 173–190

    Article  Google Scholar 

  • Arendt-Nielsen, L., Mills, K. R., andForster, A. (1989): ‘Changes in muscle fibre conduction velocity, mean power frequency, and mean EMG voltage during prolonged submaximal contractions’,Muscle Nerve,12, pp. 493–497

    Article  Google Scholar 

  • Arabadzhiev, T. I., Dimitrov, G. V., andDimitrova, N. A. (2003): ‘Simulation analysis of the ability to estimate motor unit propagation velocity non-invasively by different two-channel methods and types of multi-electrodes’,J. Electromyogr. Kinesiol.,13, pp. 403–415

    Article  Google Scholar 

  • Bigland-Ritchie, B., Donovan, E. F., andRoussos, C. S. (1981): ‘Conduction velocity and EMG power spectrum changes in fatigue of sustained maximal efforts’,J. Appl. Physiol.,51, pp. 1300–1305

    Google Scholar 

  • Bonato, P., Balestra, G., Knaflitz, M., andMerletti, R. (1990): ‘Comparison between muscle fibre conduction velocity estimation techniques: spectral matching versus crosscorrelation’. Proc. 8th ISEK Congress, pp. 19–22

  • Davies, S. W., andParker, P. A. (1987): ‘Estimation of myoelectric conduction velocity distribution’,IEEE Trans. Biomed. Eng.,34, pp. 365–374

    Article  Google Scholar 

  • Dimitrov, G. V., andDimitrova, N. A. (1974): ‘Extracellular potential field of a single striated muscle fibre immersed in anisotropic volume conductor’,Electromyogr. Clin. Neurophysiol.,14, pp. 423–436

    Google Scholar 

  • Dimitrov, G. V., Lateva, Z. C., andDimitrova, N. A. (1988): ‘Effects of changes in asymmetry, duration and propagation velocity of the intracellular potential on the power spectrum of extracellular potentials produced by an excitable fibre’,Electromyogr. Clin. Neurophysiol.,28, pp. 93–100

    Google Scholar 

  • Dimitrova, N. A., andDimitrov, G. V. (2003): ‘Interpretation of EMG changes with fatigue: facts, pitfalls, and fallacies’,J. Electromyogr. Kinesiol.,13, pp. 13–36

    Article  Google Scholar 

  • Farina, D., andMerletti, R. (2000): ‘Comparison of algorithms for estimation of EMG variables during voluntary isometric contractions’,J. Electromyogr. Kinesiol.,10, pp. 337–349

    Article  Google Scholar 

  • Farina, D., Fortunato, E., andMerletti, R. (2000): ‘Noninvasive estimation of motor unit conduction velocity distribution using linear electrode arrays’,IEEE Trans. Biomed. Eng.,47, pp. 380–388

    Article  Google Scholar 

  • Farina, D., Muhammad, W., Fortunato, E., Meste, O., Merletti, R., andRix, H. (2001): ‘Estimation of single motor unit conduction velocity from surface electromyogram signals detected with linear electrode arrays’,Med. Biol. Eng. Comput.,39, pp. 225–236

    Article  Google Scholar 

  • Farina, D., Fosci, M., andMerletti, R. (2002a): ‘Motor unit recruitment strategies investigated by surface EMG variables’,J. Appl. Physiol.,92, pp. 235–247

    Article  Google Scholar 

  • Farina, D., Arendt-Nielsen, L., Merletti, R., andGraven-Nielsen, T. (2002b): ‘Assessment of single motor unit conduction velocity during sustained contractions of the tibialis anterior muscle with advanced spike triggered averaging’,J. Neurosci. Meth.,30, pp. 1–12

    Article  Google Scholar 

  • Farina, D., andMerletti, R. (2003): ‘A novel approach for estimating muscle fibre conduction velocity by spatial and temporal filtering of surface EMG signals’,IEEE Trans. Biomed. Eng.,50, pp. 1340–1351

    Article  Google Scholar 

  • Farina, D., Pozzo, M., Merlo, E., Bottin, A., andMerletti, R. (2004a): ‘Assessment of muscle fibre conduction velocity from surface EMG signals during fatiguing dynamic contractions’,IEEE Trans. Biomed. Eng., (in press)

  • Farina, D., Arendt-Nielsen, L., Merletti, R., andGraven-Nielsen, T. (2004b). ‘The effect of experimental muscle pain on motor unit firing rate and conduction velocity’,J. Neurophysiol.,91, pp. 1250–1259

    Article  Google Scholar 

  • Farina, D., Zagari, D., Gazzoni, M., andMerletti, R. (2004c): ‘Reproducibility of muscle fibre conduction velocity estimates using multi-channel surface EMG techniques’,Muscle Nerve,29, pp. 282–291

    Article  Google Scholar 

  • Farina, D., Mesin, L., Martina, S., andMerletti, R. (2004d): ‘A surface EMG generation model with multi-layer cylindrical description of the volume conductor’,IEEE Trans. Biomed. Eng.,51, pp. 415–426

    Article  Google Scholar 

  • Farina, D., Mesin, L., Martina, S., andMerletti, R. (2004e): ‘Comparison of spatial filter selectivity in surface myoelectric signal detection—Influence of the volume conductor model’,Med. Biol. Eng. Comput.,42, pp. 114–120

    Article  Google Scholar 

  • Farina, D., Merletti, R., andEnoka, R. M. (2004f): ‘The surface electromyogram as a window into the nervous system-not exactly’,J. Appl. Physiol.,96, pp. 1486–1495

    Article  Google Scholar 

  • Farina, D., Mesin, L., andMartina, S. (2004g): ‘Advances in surface electromyographic signal simulation with analytical and numerical descriptions of the volume conductor’,Med. Biol. Eng. Comput.,42, pp. 467–476

    Article  Google Scholar 

  • Farina, D., andMerletti, R. (2004): ‘Estimation of average muscle fibre conduction velocity from two-dimensional surface EMG recordings’,J. Neurosci. Meth.,134, pp. 199–208

    Article  Google Scholar 

  • Gonzalez-Cueto, J. A., andParker, P. A. (2002): ‘Deconvolution estimation of motor unit conduction velocity distribution’,IEEE Trans. Biomed. Eng.,49, pp. 955–962

    Article  Google Scholar 

  • Gydikov, A., Gerilovsky, L., andDimitrov, G. V. (1976a): ‘Volume conducted motor unit potentials in human triceps surae’,Electromyogr: Clin. Neurophysiol.,16, pp. 569–586

    Google Scholar 

  • Gydikov, A., Dimitrov, G., Kosarov, D., andDimitrova, N. (1976b): ‘Functional differentiation of motor units in human opponens pollicis muscle’,Exp. Neurol.,50, pp. 36–47

    Article  Google Scholar 

  • Gydikov, A., Kosarov, D., andDimitrov, G. V. (1979): ‘Length of the summated depolarized area and duration of the depolarizing and repolarizing processes in the motor unit under different conditions’,Electromyogr: Clin. Neurophysiol.,19, pp. 229–248

    Google Scholar 

  • Gydikov, A. (1981): ‘Spreading of potentials along the muscle, investigated by averaging of the summated EMG’,Electromyogr. Clin. Neurophysiol.,21, pp. 525–538

    Google Scholar 

  • Gydikov, A., Kostov, K., Kossev, A., andKosarov, D. (1984): ‘Estimation of the spreading velocity and the parameters of the muscle potentials by averaging of the summated electromyogram’,Electromyogr. Clin. Neurophysiol.,24, pp. 191–212

    Google Scholar 

  • Hogrel, J. Y., andDuchene, J. (2002): ‘Motor unit conduction velocity distribution estimation: assessment of two short-term processing methods’,Med. Biol. Eng. Comput.,40, pp. 253–259

    Article  Google Scholar 

  • Houtman, C. J., Stegeman, D. F., van Dijk, J. P., andZwarts, M. J. (2003): ‘Changes in muscle fibre conduction velocity indicate recruitment of distinct motor unit populations’,J. Appl. Physiol.,95, pp. 1045–1054

    Google Scholar 

  • Hunter, I. W., Kearney, R. E., andJones, L. A. (1987): ‘Estimation of the conduction velocity of muscle action potentials using phase and impulse response function techniques’,Med. Biol. Eng. Comput.,25, pp. 121–126

    Article  Google Scholar 

  • Johnson, D. H., andDuolgeon, D. E. (1993): ‘Array signal processing—Concepts and techniques’ (Prentice Hall Signal Processing series, 1993), Oppenheim, A. V. (Series Ed.)

  • Lanzetta, M., Farina, D., Pozzo, M., Bottin, A., andMerletti, R. (2004): ‘Motor unit reinnervation and control properties in intrinsic muscles of a transplanted hand’. Proc. XVth ISEK Congress, Boston, (in press)

  • Laterza, F., Lo Conte, L., Mattacchione, M., andMerletti, R. (1998): ‘Information in the surface EMG spectral content’,SENIAM Deliverable,6, pp. 109–116

    Google Scholar 

  • Lindstrom, L., Magnusson, R., andPetersén, I. (1970): ‘Muscular fatigue and action potential conduction velocity changes studied with frequency analysis of EMG signals’,Electromyography,10, pp. 341–356

    Google Scholar 

  • Lindstrom, L., Magnusson, R., andPetersén, I. (1971): ‘The ‘dip phenomenon’ in power spectra of EMG signals’,Electroencephalogr. Clin. Neurophysiol.,30, pp. 259–260

    Google Scholar 

  • Lindstrom, L., Kadefors, R., andPetersén, I. (1977): ‘An electromyographic index for localized muscle fatigue’,J. Appl. Physiol.,43, pp. 750–754

    Google Scholar 

  • Lindstrom, L., andMagnusson, R. (1977): ‘Interpretation of myoelectric power spectra: a model and its applications’,Proc. IEEE,65, pp. 653–662

    Article  Google Scholar 

  • Linssen, W. H., Stegeman, D. F., Joosten, E. M., Merks, H. J., ter Laak, H. J., Binkhorst, R. A., andNotermans, S. L. (1991): ‘Force and fatigue in human type I muscle fibres. A surface EMG study in patients with congenital myopathy and type I fibre predominance’,Brain,114, pp. 2123–2132

    Article  Google Scholar 

  • Linssen, W. H., Stegeman, D. F., Joosten, E. M., van't Hof, M. A., Binkhorst, R. A., andNotermans, S. L. (1993): ‘Variability and interrelationships of surface EMG parameters during local muscle fatigue’,Muscle Nerve,16, pp. 849–856

    Article  Google Scholar 

  • Lo Conte, L. R., Merletti, R., andSandri, G. V. (1994): ‘Hermite expansions of compact support waveforms: applications to myoelectric signals’,IEEE Trans. Biomed. Eng.,41, pp. 1147–1159

    Article  Google Scholar 

  • Lo Conte, L. R., andMerletti, R. (1995): ‘Advances in processing of surface myoelectric signals: Part 2’,Med. Biol. Eng. Comput.,33, pp. 373–384

    Article  Google Scholar 

  • Lynn, P. A. (1979): ‘Direct on-line estimation of muscle fiber conduction velocity by surface electromyography’,IEEE Trans. Biomed. Eng.,26, pp. 564–571

    Article  Google Scholar 

  • Masuda, T., Miyano, H., andSadoyama, T. (1985): ‘The position of innervation zones in the biceps brachii investigated by surface electromyography’,IEEE Trans. Biomed. Eng.,32, pp. 36–42

    Article  Google Scholar 

  • Masuda, T., andSadoyama, T. (1987): ‘Skeletal muscles from which the propagation of motor unit action potentials is detectable with a surface electrode array’,Electroencephalogr. Clin. Neurophysiol.,67, pp. 421–427

    Article  Google Scholar 

  • McGill, K. C., andDorfman, L. J. (1984): ‘High-resolution alignment of sampled waveforms’,IEEE Trans. Biomed. Eng.,31, pp. 462–468

    Article  Google Scholar 

  • McKinley, C. A., andParker, P. A. (1991): ‘A beamformer for the acquisition of evoked potentials’,IEEE Trans. Biomed. Eng.,38, pp. 379–382

    Article  Google Scholar 

  • McVicar, G. N., andParker, P. A. (1988): ‘Spectrum dip estimator of nerve conduction velocity’,IEEE Trans. Biomed. Eng.,35, pp. 1069–1076

    Article  Google Scholar 

  • Merletti, R., Knaflitz, M., andDe Luca, C. J. (1990): ‘Myoelectric manifestations of fatigue in voluntary and electrically elicited contractions’,J. Appl. Physiol.,69, pp. 1810–1820

    Google Scholar 

  • Merletti, R., andLo Conte, L. R. (1995): ‘Advances in processing of surface myoelectric signals: Part 1’,Med. Biol. Eng. Comput.,33, pp. 362–372

    Article  Google Scholar 

  • Merletti, R., Farina, D., Gazzoni, M., andSchieroni, M. P. (2002): ‘Effect of age on muscle functions investigated with surface electromyography’,Muscle Nerve,25, pp. 65–76

    Article  Google Scholar 

  • Mesin, L., Farina, D., andMerletti, R. (2004): ‘Effect of local in-homogeneities in the subcutaneous tissue on muscle fiber conduction velocity estimates assessed with a novel analytical surface EMG model’. Proc. XVth ISEK Congress, Boston, (in press)

  • Muhammad, W., Meste, O., andRix, H. (2002): ‘Comparison of single and multiple time delay estimators: application to muscle fiber conduction velocity estimation’,Signal Process.,82, pp. 925–940

    Article  MATH  Google Scholar 

  • Muhammad, W., Meste, O., Rix, H., andFarina, D. (2003): ‘A pseudojoint estimation of time delay and scale factor for M-wave analysis’,IEEE Trans. Biomed. Eng.,50, pp. 459–468

    Article  Google Scholar 

  • Naeije, M., andZorn, H. (1983): ‘Estimation of the action potential conduction velocity in human skeletal muscle using the surface EMG cross-correlation technique’,Electromyogr. Clin. Neurophysiol.,23, pp. 73–80

    Google Scholar 

  • Parker, P. A., andScott, R. N. (1973): ‘Statistics of the myoelectric signal from monopolar and bipolar electrodes’,Med. Biol. Eng.,11, pp. 591–596

    Article  Google Scholar 

  • Piper, H. (1912): ‘Electrophysiologie Menschlicher Muskeln’, (Springer-Verlag, Berlin, 1912)

    Google Scholar 

  • Pozzo, M., Merlo, E., Farina, D., Antonutto, G., Merletti, R., anddi Prampero, P. E. (2003): ‘Muscle fiber conduction velocity estimated from surface EMG signals during very short explosive efforts in humans’,Muscle Nerve,29, pp. 823–833

    Article  Google Scholar 

  • Rix, H., andMalengé, J. P. (1980): ‘Detecting small variation in shape’,IEEE Trans. Syst. Man Cybern.,10, pp. 90–96

    Article  Google Scholar 

  • Rongen, G. A., van Dijk, J. P., van Ginneken, E. E., Stegeman, D. F., Smits, P., andZwarts, M. J. (2002): ‘Repeated ischaemic isometric exercise increases muscle fibre conduction velocity in humans: involvement of Na(+)−K(+)-ATPase’,J. Physiol.,540, pp. 1071–1078

    Article  Google Scholar 

  • Sadoyama, T., Masuda, T., andMiyano, T. (1985): ‘Optimal conditions for the measurement of muscle fiber conduction velocity using surface electrode arrays’,Med. Biol. Eng. Comput.,23, pp. 339–342

    Article  Google Scholar 

  • Sadoyama, T., Masuda, T., Miyata, H., andKatsuta, S. (1988): ‘Fibre conduction velocity and fibre composition in human vastus lateralis’,Eur. J. Appl. Physiol. Occup. Physiol.,57, pp. 767–771

    Article  Google Scholar 

  • Schneider, J., Rau, G., andSilny, J. (1989): ‘A noninvasive EMG technique for investigating the excitation propagation in single motor units’,Electromyogr. Clin. Neurophysiol.,29, pp. 273–280

    Google Scholar 

  • Schneider, J., Silny, J., andRau, G. (1991): ‘Influence of tissue inhomogeneities on noninvasive muscle fiber conduction velocity measurements—investigated by physical and numerical modeling’,IEEE Trans. Biomed. Eng.,38, pp.851–860

    Article  Google Scholar 

  • Schulte, E., Farina, D., Rau, G., Merletti, R., andDisselhorst-Klug, C. (2003): ‘Single motor unit analysis from spatially filtered surface electromyogram signals. Part 2: conduction velocity estimation’,Med. Biol. Eng. Comput.,41, pp. 338–345

    Article  Google Scholar 

  • Spinelli, E., Felice, C. J., Mayosky, M., Politti, J. C., andValentinuzzi, M. E. (2001): ‘Propagation velocity measurement: autocorrelation technique applied to the electromyogram’,Med. Biol. Eng. Comput.,39, pp. 590–593

    Article  Google Scholar 

  • Stulen, F. B., andDe Luca, C. J. (1981): ‘Frequency parameters of the myoelectric signals as a measure of muscle conduction velocity’,IEEE Trans. Biomed. Eng.,28, pp. 515–523

    Article  Google Scholar 

  • van der Hoeven, J. H., Zwarts, M. J., andvan Weerden, T. W. (1993): ‘Muscle fiber conduction velocity in amyotrophic lateral sclerosis and traumatic lesions of the plexus brachialis’,Electroencephalogr. Clin. Neurophysiol.,89, pp. 304–310

    Article  Google Scholar 

  • van der Hoeven, J. H., Links, T. P., Zwarts, M. J., andvan Weerden, T. W. (1994): ‘Muscle fiber conduction velocity in the diagnosis of familial hypokalemic periodic paralysis-invasive versus surface determination’,Muscle Nerve,17, pp. 898–905

    Article  Google Scholar 

  • Zwarts, M. J., Drost, G., andStegeman, D. F. (2000): ‘Recent progress in the diagnostic use of surface EMG for neurological diseases’,J. Electromyogr. Kinesiol.,10, pp. 287–291

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to D. Farina.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Farina, D., Merletti, R. Methods for estimating muscle fibre conduction velocity from surface electromyographic signals. Med. Biol. Eng. Comput. 42, 432–445 (2004). https://doi.org/10.1007/BF02350984

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02350984

Keywords

Navigation