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 journalArticle

14 Citations (Scopus)

Abstract

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
Volume12
Issue number1
DOIs
Publication statusPublished - 2002

Fingerprint

Nerve Fibers
Action Potentials
Median Nerve
Elbow
Least-Squares Analysis
Wrist
Peripheral Nerves
Electric Stimulation
Electrodes
Skin

Keywords

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

ASJC Scopus subject areas

  • Orthopedics and Sports Medicine

Cite this

Estimation of the conduction velocity distribution of human sensory nerve fibers. / Morita, G.; Tu, Y. X.; Okajima, Y.; Honda, S.; Tomita, Y.

In: Journal of Electromyography and Kinesiology, Vol. 12, No. 1, 2002, p. 37-43.

Research output: Contribution to journalArticle

Morita, G. ; Tu, Y. X. ; Okajima, Y. ; Honda, S. ; Tomita, Y. / Estimation of the conduction velocity distribution of human sensory nerve fibers. In: Journal of Electromyography and Kinesiology. 2002 ; Vol. 12, No. 1. pp. 37-43.
@article{b4e5dee16fe64116a7f39a5c44a18e7b,
title = "Estimation of the conduction velocity distribution of human sensory nerve fibers",
abstract = "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.",
keywords = "Compound nerve action potential, Conduction distance, Conduction velocity distribution, Fibonacci search, Regularized non-negative least squares method, Smoothness constraint",
author = "G. Morita and Tu, {Y. X.} and Y. Okajima and S. Honda and Y. Tomita",
year = "2002",
doi = "10.1016/S1050-6411(01)00029-3",
language = "English",
volume = "12",
pages = "37--43",
journal = "Journal of Electromyography and Kinesiology",
issn = "1050-6411",
publisher = "Elsevier Limited",
number = "1",

}

TY - JOUR

T1 - Estimation of the conduction velocity distribution of human sensory nerve fibers

AU - Morita, G.

AU - Tu, Y. X.

AU - Okajima, Y.

AU - Honda, S.

AU - Tomita, Y.

PY - 2002

Y1 - 2002

N2 - 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.

AB - 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.

KW - Compound nerve action potential

KW - Conduction distance

KW - Conduction velocity distribution

KW - Fibonacci search

KW - Regularized non-negative least squares method

KW - Smoothness constraint

UR - http://www.scopus.com/inward/record.url?scp=0036170635&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0036170635&partnerID=8YFLogxK

U2 - 10.1016/S1050-6411(01)00029-3

DO - 10.1016/S1050-6411(01)00029-3

M3 - Article

C2 - 11804810

AN - SCOPUS:0036170635

VL - 12

SP - 37

EP - 43

JO - Journal of Electromyography and Kinesiology

JF - Journal of Electromyography and Kinesiology

SN - 1050-6411

IS - 1

ER -