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Automatic detection of the wake and stage 1 sleep stages using the EEG sub-epoch approach

机译:使用EEG子时代方法自动检测唤醒和1期睡眠阶段

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摘要

Studies by Rechtschaffen and Kales (R&K), rely on 30-sec epochs to score sleep stages. In this paper, we introduce a new approach based on three consecutive and non-consecutive 6-sec sub-epochs for the detection of the wake stage and stage 1 sleep. The Relative Spectral Energy Band (RSEB) is used as a feature extraction from the electroencephalographic (EEG) signal. Spectral estimation is performed using non-parametric and parametric methods. We then compared the performance of the conventional 30-sec epochs with the three consecutive and non-consecutive 6-sec epochs. The outcomes of this study showed that while the accuracy varies between subjects, the non-parametric method proved to be more effective with stage 1 sleep detection and the parametric method was more effective for wake stage detection. The non-consecutive sub-epoch method was more effective and consecutive method was least effective in non-parametric stage 1 detection. Alternatively, the 30-second epoch method was most effective for parametric wake stage detection.
机译:Rechtschaffen和Kales(R&K)的研究依靠30秒的时间来记录睡眠阶段。在本文中,我们介绍了一种基于三个连续且非连续的6秒子周期的新方法,用于检测唤醒阶段和阶段1睡眠。相对光谱能带(RSEB)用作从脑电图(EEG)信号中提取的特征。使用非参数和参数方法执行频谱估计。然后,我们将传统的30秒时代与三个连续且非连续的6秒时代的效果进行了比较。这项研究的结果表明,尽管受试者之间的准确性有所不同,但非参数方法被证明对于1期睡眠检测更为有效,而参数方法对于唤醒阶段检测更为有效。在非参数阶段1检测中,非连续子历元方法更有效,而连续法则效果最低。另外,30秒纪元方法对于参数唤醒阶段检测最有效。

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