Department of Neurology, University Medical Center Groningen, Groningen, The Netherlands.
Department of Neurology, University Medical Center Groningen, Groningen, The Netherlands.
Clin Neurophysiol. 2018 Jan;129(1):13-20. doi: 10.1016/j.clinph.2017.10.002. Epub 2017 Oct 14.
To distinguish tremor subtypes using wavelet coherence analysis (WCA). WCA enables to detect variations in coherence and phase difference between two signals over time and might be especially useful in distinguishing functional from organic tremor.
In this pilot study, polymyography recordings were studied retrospectively of 26 Parkinsonian (PT), 26 functional (FT), 26 essential (ET), and 20 enhanced physiological (EPT) tremor patients. Per patient one segment of 20 s in duration, in which tremor was present continuously in the same posture, was selected. We studied several coherence and phase related parameters, and analysed all possible muscle combinations of the flexor and extensor muscles of the upper and fore arm. The area under the receiver operating characteristic curve (AUC-ROC) was applied to compare WCA and standard coherence analysis to distinguish tremor subtypes.
The percentage of time with significant coherence (PTSC) and the number of periods without significant coherence (NOV) proved the most discriminative parameters. FT could be discriminated from organic (PT, ET, EPT) tremor by high NOV (31.88 vs 21.58, 23.12 and 10.20 respectively) with an AUC-ROC of 0.809, while standard coherence analysis resulted in an AUC-ROC of 0.552.
EMG-EMG WCA analysis might provide additional variables to distinguish functional from organic tremor.
WCA might prove to be of additional value to discriminate between tremor types.
使用小波相干分析（WCA）区分震颤亚型。WCA 能够检测两个信号随时间的相干性和相位差变化，可能特别有助于区分功能性震颤和器质性震颤。
在这项初步研究中，回顾性研究了 26 例帕金森病（PT）、26 例功能性（FT）、26 例特发性（ET）和 20 例增强生理性（EPT）震颤患者的肌电图记录。为每位患者选择持续同一姿势出现震颤的 20 秒持续时间的一段记录。我们研究了几个相干性和相位相关参数，并分析了上、前臂屈肌和伸肌的所有可能的肌肉组合。应用受试者工作特征曲线（ROC）下面积（AUC-ROC）比较 WCA 和标准相干分析区分震颤亚型的能力。
有显著相干性的时间百分比（PTSC）和无显著相干性的周期数（NOV）证明是最具鉴别力的参数。FT 通过高 NOV（分别为 31.88、21.58、23.12 和 10.20）与有机震颤（PT、ET、EPT）区分开来，AUC-ROC 为 0.809，而标准相干分析的 AUC-ROC 为 0.552。
肌电图-肌电图 WCA 分析可能提供额外的变量来区分功能性和器质性震颤。
WCA 可能被证明是区分震颤类型的附加价值。
