Phasic Electromyographic Metric detection based on wavelet analysis.
Phasic Electromyographic Metric detection based on wavelet analysis.
复制标题
基于小波分析的相位肌电指标检测。
DOI：
10.1109/med.2011.5983202
复制
发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Bliwise,DonaldL
中科院分区：
文献类型：
--
作者：
Fairley,JacquelineA;Georgoulas,George;Stylios,ChrystostomosD;Vachtsevanos,George;Rye,DavidB;Bliwise,DonaldL
相性肌电测量（PEM）最近被引入作为区分帕金森病（PD）患者与对照、具有快速眼动障碍（RBD）病史的非PD患者与对照以及具有早期和晚期疾病的PD患者的敏感指标。然而，通过目视检查进行PEM评估是一个繁琐且耗时的过程。因此，需要一种可靠的自动化方法，以提高PEM作为跟踪PD进展的可靠且有效的临床工具的利用率。在这项研究中，提出了一种自动检测PEM的方法，基于使用信号分析和模式识别技术。结果表明，PEM的自动识别程序是可行的。
The Phasic Electromyographic Metric (PEM) has been recently introduced as a sensitive indicator to differentiate Parkinson's Disease (PD) patients from controls, non-PD patients with a history of Rapid Eye Movement Disorder (RBD) from controls, and PD patients with early and late stage disease. However, PEM assessment through visual inspection is a cumbersome and time consuming process. Therefore, a reliable automated approach is required so as to increase the utilization of PEM as a reliable and efficient clinical tool to track PD progression. In this study an automated method for the detection of PEM is presented, based on the use of signal analysis and pattern recognition techniques. The results are promising indicating that an automatic PEM identification procedure is feasible.