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Time-frequency analysis of human sleep EEG and its application to feature extraction about biological rhythm

机译:人类睡眠脑电图的时频分析及其应用于生物节律的特征提取

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We have developed so far an automatic discrimination system of human sleep EEG stages based on a waveshape recognition method. These systems were able to detect discrete stages (Stage MT, W, 1, 2, 3, 4, REM). However, they are not sufficient to extract much information in detail. Therefore, in order to extract more precise information for sleep stages, we have tried to analyze the sleep EEG in its time-frequency domain by employing a continuous wavelet transform based on Gabor wavelets. In this paper, a modified wavelet transform method is proposed. It has the feature that the damping coefficient of Gabor wavelets is adjusted by a sigmoid function. In the experiments, compared with the ordinary wavelet transform with some constant damping coefficients, it has been confirmed that the modified wavelet transform method can have the adequate frequency resolution for analyzing frequency components of sleep EEG.
机译:到目前为止,我们已经开发了基于波莎识别方法的人类睡眠脑台阶段的自动辨别系统。这些系统能够检测离散阶段(阶段MT,W,1,2,3,4,REM)。然而,它们不足以详细提取许多信息。因此,为了提取更精确的睡眠阶段信息,我们尝试通过采用基于Gabor小波的连续小波变换来分析其时频域中的睡眠脑电图。本文提出了一种改进的小波变换方法。它具有通过S形函数调节Gabor小波的阻尼系数的特征。在实验中,与具有一些恒定阻尼系数的普通小波变换相比,已经证实了改进的小波变换方法可以具有适当的频率分辨率,用于分析睡眠脑电图的频率分量。

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