Motor unit action potential duration, II: a new automatic measurement method based on the wavelet transform
Ver/
Fecha
2007Autor
Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión aceptada / Onetsi den bertsioa
Impacto
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nodoi-noplumx
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Resumen
To present and evaluate a new algorithm, based on the
wavelet transform, for the automatic measurement of motor unit
action potential (MUAP) duration. A total of 240 MUAPs were
studied. The waveform of each MUAP was wavelet-transformed,
and the start and end points were estimated by regarding the maxima
and minima points in a particular scale of the wavelet transform. The
results of the new ...
[++]
To present and evaluate a new algorithm, based on the
wavelet transform, for the automatic measurement of motor unit
action potential (MUAP) duration. A total of 240 MUAPs were
studied. The waveform of each MUAP was wavelet-transformed,
and the start and end points were estimated by regarding the maxima
and minima points in a particular scale of the wavelet transform. The
results of the new method were compared with the gold standard of
duration marker positions obtained by manual measurement. The
new method was also compared with a conventional algorithm,
which we had found to be best in a previous comparative study. To
evaluate the new method against manual measurements, the dispersion
of automatic and manual duration markers were analyzed in a
set of 19 repeatedly recorded MUAPs. The differences between the
new algorithm’s marker positions and the gold standard of duration
marker positions were smaller than those observed with the conventional
method. The dispersion of the new algorithm’s marker positions
was slightly less than that of the manual one. Our new method
for automatic measurement of MUAP duration is more accurate than
other available algorithms and more consistent than manual measurements. [--]
Materias
Motor unit action potential,
Duration,
Quantitative electromyography,
Wavelet transform
Editor
Lippincott, Williams & Wilkins
Publicado en
Journal of Clinical Neurophysiology, 24 (1):59-69, February 2007
Departamento
Universidad Pública de Navarra. Departamento de Ingeniería Eléctrica y Electrónica /
Universidad Pública de Navarra. Departamento de Estadística e Investigación Operativa /
Nafarroako Unibertsitate Publikoa. Ingeniaritza Elektrikoa eta Elektronikoa Saila /
Nafarroako Unibertsitate Publikoa. Estatistika eta Ikerketa Operatiboa Saila
Entidades Financiadoras
This work was funded by the Instituto de Salud Carlos
III (Project PIO21510) and by the Ministerio de Ciencia y
Tecnología (Project BFM 2001-1667-03-01).