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肌电图干扰模式的自动分析。第二部分:健康对照者及某些神经肌肉疾病患者的研究结果。

Automatic analysis of the electromyographic interference pattern. Part II: Findings in control subjects and in some neuromuscular diseases.

作者信息

Nandedkar S D, Sanders D B, Stålberg E V

出版信息

Muscle Nerve. 1986 Jul-Aug;9(6):491-500. doi: 10.1002/mus.880090604.

Abstract

The electromyographic (EMG) interference pattern (IP) was measured in the biceps muscle of 16 normal male and 17 normal female subjects. The activity, upper centile amplitude (UCA), and the number of small segments (NSS) (defined in a companion paper) were measured from 500-msec epochs of the IP. The normal values of these features were defined separately for men and women by plotting the UCA and NSS values against activity for each epoch and defining an area on these plots, called a "cloud," that contained more than 90% of the datum points from each study. The mean deviation of the individual datum points from the overall mean values was also calculated for each study. A study in one muscle is considered to be normal if more than 90% of the datum points from that muscle are within the normal clouds and the deviation values are within their normal range. In patients with neuropathy, the characteristic pattern was increased UCA with normal or decreased NSS. In patients with myopathy, NSS was increased and the UCA was normal or decreased. In all studies, the interpretations of the IP from the plots agreed with qualitative assessments of the IP made independently by an electromyographer. The use of these features to understand and quantitate the changes in the motor units produced by disease is demonstrated by serial studies performed in a patient with motor neuron disease.

摘要

在16名正常男性和17名正常女性受试者的肱二头肌中测量了肌电图(EMG)干扰模式(IP)。从IP的500毫秒时间段中测量活动、上百分位数幅度(UCA)和小段数量(NSS)(在一篇配套论文中定义)。通过针对每个时间段将UCA和NSS值与活动作图,并在这些图上定义一个称为“云”的区域,该区域包含每项研究中超过90%的数据点,分别为男性和女性定义了这些特征的正常值。还为每项研究计算了各个数据点相对于总体平均值的平均偏差。如果一块肌肉中超过90%的数据点在正常云内且偏差值在其正常范围内,则认为该肌肉的一项研究是正常的。在患有神经病变的患者中,特征模式是UCA增加而NSS正常或降低。在患有肌病的患者中,NSS增加而UCA正常或降低。在所有研究中,从图中对IP的解释与肌电图师独立进行的IP定性评估一致。对一名运动神经元疾病患者进行的系列研究证明了使用这些特征来理解和量化疾病导致的运动单位变化。

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