Schlotthauer Gastón, Di Persia Leandro E, Larrateguy Luis D, Milone Diego H
Lab. of Signals and Nonlinear Dynamics, Facultad de Ingeniería, Universidad Nacional de Entre Ríos, Argentina; National Council of Scientific and Technical Research (CONICET), Argentina.
Research Center for Signals, Systems and Computational Intelligence (sinc(i)), Facultad de Ingeniería y Ciencias Hídricas, Universidad Nacional del Litoral, Argentina; National Council of Scientific and Technical Research (CONICET), Argentina.
Med Eng Phys. 2014 Aug;36(8):1074-80. doi: 10.1016/j.medengphy.2014.05.008. Epub 2014 Jun 13.
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.
通过脉搏血氧饱和度信号检测血氧饱和度下降对于睡眠呼吸暂停的诊断非常重要。利用血氧饱和度下降的计数,可以构建一个指标来辅助诊断重度阻塞性睡眠呼吸暂停低通气综合征。拥有自动检测方法以筛查该综合征很重要,这可以减少对基于昂贵多导睡眠图研究的需求。本文提出了一种基于脉搏血氧饱和度信号经验模态分解的新型识别方法。血氧饱和度下降会产生一种非常特殊的波形模式,该模式在分解的各模态中被提取出来。利用这些信息,构建了一个基于适当选择的阈值和一组简单规则的检测器。由这些检测结果构建的氧饱和度下降指数产生了一个用于阻塞性睡眠呼吸暂停低通气综合征的检测器,其具有高灵敏度(0.838)和特异性(0.855),并且比标准的血氧饱和度下降检测方法产生更好的结果。