Estimation of the conduction velocity distribution of human sensory nerve fibers

G. Morita, Y. X. Tu, Y. Okajima, S. Honda, Y. Tomita

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)


A new method for estimating the distribution of conduction velocities (DCV) of peripheral nerve fibers has been developed. It also enables estimation of single nerve fiber action potential (SFAP), which agrees with the physiological knowledge. Two compound nerve action potentials (CAPs) elicited by electrical stimulation of a nerve bundle were recorded at different conduction distances. The distances between the stimulation and recording electrodes were measured on the skin surface along the nerve bundle. Starting with an arbitrary SFAP, the first estimated DCV was calculated from a CAP by the regularized non-negative least squares method. The next SFAP was then calculated by deconvolution of the other CAP and the estimated DCV. A lowpass filter with an appropriate cutoff frequency was used to obtain better conversion. The process was iterated until the CAP error defined as |CAPcalculated-CAP|2 was small enough. The conduction distances contained errors in measurement, especially in the distal segment, that distorted the estimated results. The Fibonacci search, therefore, was adopted to optimize the distance according to the CAP error. The accuracy of this method was demonstrated by a simulation study performed with two CAPs calculated from an arbitrary bimodal DCV and a biphasic SFAP to which a Gaussian white noise was added. The reliability of this method was checked in normal subjects by recording a pair of CAPs elicited by stimulation of the median nerve at the wrist and the elbow.

Original languageEnglish
Pages (from-to)37-43
Number of pages7
JournalJournal of Electromyography and Kinesiology
Issue number1
Publication statusPublished - 2002 Feb 18


  • Compound nerve action potential
  • Conduction distance
  • Conduction velocity distribution
  • Fibonacci search
  • Regularized non-negative least squares method
  • Smoothness constraint

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Biophysics
  • Clinical Neurology


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