Literature DB >> 10743780

Noninvasive estimation of motor unit conduction velocity distribution using linear electrode arrays.

D Farina1, E Fortunato, R Merletti.   

Abstract

Determining the conduction velocity of motor unit action potentials is one of the most important problems in surface electromyography. The estimate of one average conduction velocity value depends on a variety of uncontrollable factors. More meaningful information is obtained from the estimation of the distribution of the different delays in the myoelectric signals. A solution to the problem is the separation and characterization of the individual components propagating at different velocities. A technique, based on surface electrode array recording, is proposed to estimate motor unit conduction velocity distribution. The method consists in the identification of the single action potentials in the time scale domain (with the continuous wavelet transform) and in the estimation of their conduction velocities based on the beamforming algorithm. The performances of the technique have been evaluated using simulated and real myoelectric signals. The results demonstrate that the technique is accurate and reliable. The method may be useful for the diagnosis of neuromuscular disorders, for the monitoring of muscle fatigue and for noninvasive investigation of individual motor units.

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Year:  2000        PMID: 10743780     DOI: 10.1109/10.827303

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  25 in total

1.  Motor unit conduction velocity distribution estimation: assessment of two short-term processing methods.

Authors:  J Y Hogrel; J Duchêne
Journal:  Med Biol Eng Comput       Date:  2002-03       Impact factor: 2.602

2.  Single motor unit analysis from spatially filtered surface electromyogram signals. Part 2: conduction velocity estimation.

Authors:  E Schulte; D Farina; G Rau; R Merletti; C Disselhorst-Klug
Journal:  Med Biol Eng Comput       Date:  2003-05       Impact factor: 2.602

3.  Non-invasive assessment of single motor unit mechanomyographic response and twitch force by spike-triggered averaging.

Authors:  C Cescon; M Gazzoni; M Gobbo; C Orizio; D Farina
Journal:  Med Biol Eng Comput       Date:  2004-07       Impact factor: 2.602

Review 4.  Methods for estimating muscle fibre conduction velocity from surface electromyographic signals.

Authors:  D Farina; R Merletti
Journal:  Med Biol Eng Comput       Date:  2004-07       Impact factor: 2.602

5.  Sixty-four channel wearable acquisition system for long-term surface electromyogram recording with electrode arrays.

Authors:  M Pozzo; A Bottin; R Ferrabone; R Merletti
Journal:  Med Biol Eng Comput       Date:  2004-07       Impact factor: 2.602

6.  Correlation-based decomposition of surface electromyograms at low contraction forces.

Authors:  A Holobar; D Zazula
Journal:  Med Biol Eng Comput       Date:  2004-07       Impact factor: 2.602

7.  Motor unit action potential rate and motor unit action potential shape properties in subjects with work-related chronic pain.

Authors:  Laura A C Kallenberg; Hermie J Hermens
Journal:  Eur J Appl Physiol       Date:  2004-09-29       Impact factor: 3.078

8.  Differences in the force/endurance relationship between young and older men.

Authors:  Ilenia Bazzucchi; Marco Marchetti; Alessandro Rosponi; Luigi Fattorini; Vincenzo Castellano; Paola Sbriccoli; Francesco Felici
Journal:  Eur J Appl Physiol       Date:  2004-12-01       Impact factor: 3.078

9.  Influence of motor unit properties on the size of the simulated evoked surface EMG potential.

Authors:  Kevin G Keenan; Dario Farina; Roberto Merletti; Roger M Enoka
Journal:  Exp Brain Res       Date:  2005-11-05       Impact factor: 1.972

10.  Signal-dependent wavelets for electromyogram classification.

Authors:  A Maitrot; M F Lucas; C Doncarli; D Farina
Journal:  Med Biol Eng Comput       Date:  2005-07       Impact factor: 2.602

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