Vial Felipe, Attaripour Sanaz, McGurrin Patrick, Hallett Mark
Human Motor Control Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
Facultad de Medicina Clínica Alemana Universidad del Desarrollo, Santiago, Chile.
Clin Neurophysiol Pract. 2020 Jan 25;5:38-42. doi: 10.1016/j.cnp.2019.12.001. eCollection 2020.
The back-average technique is very useful to study the relation between the activity in the cortex and the muscles. It has two main clinical applications, Bereitschaftspotential (BP) recording and myoclonus studies. The BP is a slow wave negativity originating in the supplementary motor cortex and premotor cortex that precedes voluntary movements. This wave also precedes involuntary movements in functional movement disorders (FMD), and it can be used as a helpful diagnostic tool. For the myoclonus studies, the back-average technique is very important to help localizing the source of the myoclonus. The hardware needed to do BP or myoclonus studies is standard and available in any electrophysiology lab, but there are not many software solutions to do the analysis. In this article together with describing the methodology that we use for recording clinical BPs and myoclonus, we present BacAv, an online free application that we developed for the purpose of doing back-average analysis.
BacAv was developed in "R" language using Rstudio, a free integrated development environment. The recommended parameters for the data acquisition for BP recording and myoclonus studies are given in this section.
The platform was successfully developed, is able to read txt files, look for muscle bursts, segment the data, and plot the average. The parameters of the algorithm that look for the muscle bursts can be adapted according to the characteristics of the dataset.
We have developed software for clinicians who do not have sophisticated equipment to do back-averaging.
This tool will make this useful analysis method more available in a clinical environment.
反向平均技术对于研究皮质与肌肉活动之间的关系非常有用。它有两个主要的临床应用,即 Bereitschaftspotential(BP)记录和肌阵挛研究。BP 是一种起源于辅助运动皮质和运动前皮质的慢波负电位,先于自主运动出现。在功能性运动障碍(FMD)中,这种波也先于非自主运动出现,并且可作为一种有用的诊断工具。对于肌阵挛研究,反向平均技术对于帮助定位肌阵挛的来源非常重要。进行 BP 或肌阵挛研究所需的硬件是标准的,在任何电生理实验室都可获得,但用于分析的软件解决方案却不多。在本文中,我们在描述用于记录临床 BP 和肌阵挛的方法的同时,还介绍了 BacAv,这是我们为进行反向平均分析而开发的一款在线免费应用程序。
BacAv 是使用免费的集成开发环境 Rstudio 用“R”语言开发的。本节给出了 BP 记录和肌阵挛研究数据采集的推荐参数。
该平台已成功开发,能够读取 txt 文件、查找肌肉爆发信号、分割数据并绘制平均值。查找肌肉爆发信号的算法参数可根据数据集的特征进行调整。
我们为没有复杂设备进行反向平均的临床医生开发了软件。
该工具将使这种有用的分析方法在临床环境中更易于使用。