Business Department, Facultad de Económicas y Empresariales, Universidad de Navarra, Edificio Amigos, Campus Universitario, 31009, Pamplona, Navarra, Spain.
Department of Electric and Electronic Engineering, Universidad Pública de Navarra, Pamplona, Spain.
Med Biol Eng Comput. 2020 Mar;58(3):589-599. doi: 10.1007/s11517-019-02115-6. Epub 2020 Jan 9.
We present a new, automatic, correlation-based method for measuring the duration of motor unit action potentials (MUAPs). The method seeks to replicate the way an expert elctromyographer uses his or her eyes, calculating the start and end of the MUAP waveform on the basis of the degree of similarity of non-excluded discharges. We analysed 68 potentials from normal deltoid muscles during slight contraction. For each MUAP, two experienced electromyographers manually determined start and end marker positions, which were used as gold standard duration positions (GSP) in our subsequent tests. The novel method was compared with Nandedkar's method and a wavelet transform-based method. To compare the three methods, the differences between the automatic marker positions and GSPs were statistically evaluated using one-factor ANOVA, the estimated mean square error, and a Chi-square test on the numbers of automatic marker placements with gross errors. All these parameters showed smaller values for the novel method and in most of the cases were statistically significant. In addition, the parameters of the new method were subjected to a sensitivity study, showing its good performance within a range of clinically useful parameter values. The new automatic method determined start and end markers in a more accurate and reliable manner than both of the acknowledged state-of-the art methods used in our comparison study. Graphical abstract The description of a new automatic duration measurement algorithm based on the similarity among discharges of the same MUAP. This method gave better results than the Nandedkar method and a highly regarded wavelet-based method. The new correlation-based method also had the lowest rate of gross aberrant errors in automatic placements.
我们提出了一种新的、自动的、基于相关的测量运动单位动作电位(MUAP)持续时间的方法。该方法旨在复制专家肌电图仪使用眼睛的方式,根据非排除放电的相似程度计算 MUAP 波形的开始和结束。我们分析了 68 个来自正常三角肌的电位,这些电位是在轻微收缩期间记录的。对于每个 MUAP,两位有经验的肌电图仪技师手动确定起始和结束标记位置,这些位置用作我们后续测试中的金标准持续时间位置(GSP)。新方法与 Nandedkar 方法和基于小波变换的方法进行了比较。为了比较这三种方法,使用单因素方差分析、估计均方误差以及对具有明显错误的自动标记位置数量进行卡方检验,对自动标记位置与 GSP 之间的差异进行了统计学评估。所有这些参数对于新方法都显示出较小的值,并且在大多数情况下具有统计学意义。此外,新方法的参数还进行了敏感性研究,表明在一系列临床有用的参数值范围内具有良好的性能。新的自动方法比我们比较研究中使用的两种公认的最先进方法更准确和可靠地确定了起始和结束标记。