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统计运动单位数量估计:从理论到实践

Statistical motor unit number estimation: from theory to practice.

作者信息

Lomen-Hoerth Catherine, Slawnych Michael P

机构信息

Department of Neurology, University of California, San Francisco, 505 Parnassus Avenue, Room M348, San Francisco, California 94143, USA.

出版信息

Muscle Nerve. 2003 Sep;28(3):263-72. doi: 10.1002/mus.10351.

Abstract

Statistical motor unit number estimation (MUNE) is one of several experimental techniques used to estimate the number of lower motor neurons innervating a given muscle. All are fairly reproducible and have been applied successfully in monitoring neurogenic disease progression. Quantitating the number of lower motor neurons is important, since the compound muscle action potential (CMAP) and strength may not change as rapidly over time due to the confounding effect of reinnervation. MUNE techniques differ in the way they obtain samples of surface-recorded motor unit potentials (SMUP). Statistical MUNE is based on Poisson statistics, uses surface stimulation, and is useful in testing distal, superficial nerves. This review focuses on the theory behind the development of the technique, critiques the publications resulting from applying the technique in control and disease subjects, and discusses the future developments needed for clinical utility.

摘要

统计运动单位数量估计(MUNE)是用于估计支配特定肌肉的下运动神经元数量的几种实验技术之一。所有这些技术都具有相当高的可重复性,并已成功应用于监测神经源性疾病的进展。量化下运动神经元的数量很重要,因为由于再支配的混杂效应,复合肌肉动作电位(CMAP)和力量可能不会随时间迅速变化。MUNE技术在获取表面记录的运动单位电位(SMUP)样本的方式上有所不同。统计MUNE基于泊松统计,使用表面刺激,可用于测试远端浅表神经。本综述重点关注该技术发展背后的理论,对将该技术应用于对照和疾病受试者所产生的出版物进行评论,并讨论临床应用所需的未来发展。

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