Based on the well-established biopotential theory, we hypothesize that the high frequency spectral information, like that higher than 100Hz, of the EEG signal recorded in the off-the-shelf EEG sensor contains muscle tone information. We show that an existing automatic sleep stage annotation algorithm can be improved by taking this information into account. This result suggests that if possible, we should sample the EEG signal with a high sampling rate, and preserve as much spectral information as possible.

中文翻译：

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保存肌肉信息，未经过滤的脑电信号有助于区分睡眠阶段。

基于公认的生物电势理论，我们假设现成的EEG传感器中记录的EEG信号的高频频谱信息（例如高于100Hz的频谱信息）包含肌肉张力信息。我们表明，可以通过考虑此信息来改进现有的自动睡眠阶段注释算法。该结果表明，如果可能的话，我们应该以高采样率对EEG信号进行采样，并保留尽可能多的频谱信息。