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On-line estimation of myoelectric signal spectral parameters and nonstationarities detection

机译:肌电信号频谱参数的在线估计和非平稳性检测

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摘要

A method for detecting nonstationarities of random time series with an approximately Gaussian distribution of amplitudes is presented. This method is suitable for real time implementation. Some results obtained by applying them to a time series of spectral parameters of surface myoelectric signals are reported. The computerized system used to implement the detector of nonstationarity is described. This system realizes on-line estimation and display of spectral parameters, as well as detection of their nonstationarities, featuring a sampling frequency up to 20 k samples/s. A user friendly interface, fully menu driven, allows the user to select different options during the system's operation by means of hot keys. The accuracy of the system was tested by comparing its estimates with those of an off-line system, previously characterized. The estimates of spectral parameters obtained by means of the two systems were always consistent. The on-line stationarity detector was able to recognize rates of variation of the spectral parameters as small as 1% during contractions lasting 10-15 s. This sensitivity makes it suitable for clinical application.
机译:提出了一种检测振幅近似为高斯分布的随机时间序列的非平稳性的方法。此方法适合实时实施。报道了通过将它们应用于表面肌电信号的频谱参数的时间序列而获得的一些结果。描述了用于实现非平稳性检测器的计算机系统。该系统实现了频谱参数的在线估计和显示以及其非平稳性的检测,其采样频率高达20 k个样本/秒。用户友好的界面,完全由菜单驱动,允许用户在系统操作期间通过热键选择不同的选项。通过将其估计值与先前表征的离线系统的估计值进行比较来测试系统的准确性。通过两个系统获得的光谱参数的估计值始终是一致的。在线平稳性检测器能够在持续10-15 s的收缩过程中识别出光谱参数的变化率,低至1%。这种敏感性使其适合于临床应用。

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