Preprocessing surface EMG data removes voluntary muscle activity and enhances SPiQE fasciculation analysis
Preprocessing surface EMG data removes voluntary muscle activity and enhances SPiQE fasciculation analysis
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DOI：
10.1016/j.clinph.2019.09.015
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发表时间：
2020-01-01
影响因子：
4.7
通讯作者：
Shaw, C. E.
中科院分区：
文献类型：
--
作者：
Bashford, J.;Wickham, A.;Shaw, C. E.
目的：肌束震颤是肌萎缩侧索硬化症（ALS）的临床标志。表面电位量化引擎（SPiQE）是一种新的分析工具，用于从高密度表面肌电图（HDSEMG）中识别肌束震颤电位。这种方法是准确的放松录音波动的噪音水平。为了避免耗时的手动排除自愿肌肉活动，我们开发了一种方法，能够迅速排除自愿的潜力和整合与建立SPiQE pipeline.Methods：6例ALS患者，1例良性肌束震颤综合征和1例多灶性运动神经病患者进行每月30分钟HDSEMG从二头肌和腓肠肌。在MATLAB中，我们开发并比较了四个主动自愿识别（AVID）策略的性能，产生一个决策援助的最佳selection.Results：评估601一分钟的录音允许开发的敏感性，特异性和筛选策略，排除自愿的潜力。比较了165个30分钟记录的排除时间（0.2-13.1分钟）、处理时间（10.7-49.5秒）和肌束震颤频率（27.4-71.1/分钟）。整体中位肌束震颤频率为每分钟40.5（10.6-79.4 IQR）。结论：我们在此介绍AVID作为一种灵活的，有针对性的方法，以排除自愿肌肉活动HDSEMG recording.Significance：纵向量化肌束震颤在ALS可以提供独特的见解运动神经元的健康。(C)2019国际临床神经生理学联合会。由爱思唯尔公司出版
Objectives: Fasciculations are a clinical hallmark of amyotrophic lateral sclerosis (ALS). The Surface Potential Quantification Engine (SPiQE) is a novel analytical tool to identify fasciculation potentials from high-density surface electromyography (HDSEMG). This method was accurate on relaxed recordings amidst fluctuating noise levels. To avoid time-consuming manual exclusion of voluntary muscle activity, we developed a method capable of rapidly excluding voluntary potentials and integrating with the established SPiQE pipeline.Methods: Six ALS patients, one patient with benign fasciculation syndrome and one patient with multi-focal motor neuropathy underwent monthly thirty-minute HDSEMG from biceps and gastrocnemius. In MATLAB, we developed and compared the performance of four Active Voluntary IDentification (AVID) strategies, producing a decision aid for optimal selection.Results: Assessment of 601 one-minute recordings permitted the development of sensitive, specific and screening strategies to exclude voluntary potentials. Exclusion times (0.2-13.1 minutes), processing times (10.7-49.5 seconds) and fasciculation frequencies (27.4-71.1 per minute) for 165 thirty-minute recordings were compared. The overall median fasciculation frequency was 40.5 per minute (10.6-79.4 IQR).Conclusion: We hereby introduce AVID as a flexible, targeted approach to exclude voluntary muscle activity from HDSEMG recordings.Significance: Longitudinal quantification of fasciculations in ALS could provide unique insight into motor neuron health. (C) 2019 International Federation of Clinical Neurophysiology. Published by Elsevier B.V.