Rodríguez Ignacio, Gila Luis, Malanda Armando, Gurtubay Ignacio Garcia, Mallor Fermin, Gómez Sagrario, Navallas Javier, Rodríguez Javier
Departamento de Ingeniería Eléctrica y Electrónica, Universidad Pública de Navarra, Spain.
J Clin Neurophysiol. 2007 Feb;24(1):59-69. doi: 10.1097/01.wnp.0000236581.49422.c3.
The aim of this work is 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 to the gold standard of duration marker positions obtained by manual measurement. The new method was also compared to 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.
这项工作的目的是提出并评估一种基于小波变换的新算法,用于自动测量运动单位动作电位(MUAP)的持续时间。共研究了240个MUAP。对每个MUAP的波形进行小波变换,并通过考虑小波变换特定尺度下的最大值和最小值点来估计起始点和终点。将新方法的结果与通过手动测量获得的持续时间标记位置的金标准进行比较。新方法还与一种传统算法进行了比较,我们发现在之前的比较研究中该传统算法是最佳的。为了针对手动测量评估新方法,在一组19个重复记录的MUAP中分析了自动和手动持续时间标记的离散度。新算法的标记位置与持续时间标记位置金标准之间的差异小于传统方法观察到的差异。新算法标记位置的离散度略小于手动测量的离散度。我们用于自动测量MUAP持续时间的新方法比其他现有算法更准确,并且比手动测量更一致。