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Combined frequency and time domain sleep feature calculation

机译:频域和时域相结合的睡眠特征计算

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摘要

In automated sleep analysis usually both frequency and time domain features are calculated from measured physiological (EEG, EOG, EMG) signals. Usually Discrete Fourier Transform (DFT) is used for different frequency domain measures and Digital Filtering (FIR or IIR) for time domain measurement. Here we demonstrate potential usefulness of using modified inverse DFT as a step for time domain feature calculation. Analytical formulas are shown for calculating interpolation, velocity and acceleration of filtered signals. Preliminary examples of electro-oculography (EOG) signal analysis during sleep are presented. Although same results could be obtained with conventional filtering followed by numerical differentiation the presented could be useful in some cases.
机译:在自动睡眠分析中,通常从测量的生理(EEG,EOG,EMG)信号中计算出频域和时域特征。通常,离散傅里叶变换(DFT)用于不同的频域测量,而数字滤波(FIR或IIR)用于时域测量。在这里,我们展示了使用修改的逆DFT作为时域特征计算步骤的潜在实用性。显示了用于计算滤波信号的内插,速度和加速度的解析公式。介绍了睡眠期间眼电图(EOG)信号分析的初步示例。尽管使用常规滤波后再进行数值微分可以获得相同的结果,但在某些情况下提出的方法可能有用。

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