脉搏血氧饱和度的经验模态分解法筛查阻塞性睡眠呼吸暂停
Screening of Obstructive Sleep Apnea with Empirical Mode Decomposition of Pulse Oximetry
摘要：
检测脉搏血氧饱和度信号的去饱和度对于睡眠呼吸暂停的诊断非常重要。利用饱和度下降的计数，可以建立一个指数，以帮助诊断阻塞性睡眠呼吸暂停低通气综合征的严重病例。重要的是要有自动检测方法，允许筛查这种综合征，减少需要昂贵的多导睡眠图为基础的研究。提出了一种基于经验模态分解的脉搏血氧饱和度信号识别方法。去饱和产生了一个非常具体的波形，该波形在分解模式中被提取。使用这些信息，基于适当选择的阈值和一组简单规则的检测器被构建。从这些检测构建的氧去饱和指数产生了具有高灵敏度（$0.838$）和特异性（$0.855$）的阻塞性睡眠呼吸暂停低通气综合征检测器，并且产生比标准去饱和检测方法更好的结果。
英文摘要：
Detection of desaturations on the pulse oximetry signal is of great importance for the diagnosis of sleep apneas. Using the counting of desaturations, an index can be built to help in the diagnosis of severe cases of obstructive sleep apnea-hypopnea syndrome. It is important to have automatic detection methods that allows the screening for this syndrome, reducing the need of the expensive polysomnography based studies. In this paper a novel recognition method based on the empirical mode decomposition of the pulse oximetry signal is proposed. The desaturations produce a very specific wave pattern that is extracted in the modes of the decomposition. Using this information, a detector based on properly selected thresholds and a set of simple rules is built. The oxygen desaturation index constructed from these detections produces a detector for obstructive sleep apnea-hypopnea syndrome with high sensitivity ($0.838$) and specificity ($0.855$) and yields better results than standard desaturation detection approaches.
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