Zhu Xin, Chen Wenxi, Nemoto Tetsu, Kanemitsu Yumi, Kitamura Kei-Ichiro, Yamakoshi Ken-Ichi
University of Aizu, Aizu-wakamatsu, Fukushima 965-8580, Japan.
Conf Proc IEEE Eng Med Biol Soc. 2005;2005:5869-72. doi: 10.1109/IEMBS.2005.1615825.
A real-time noninvasive and unconstrained method is proposed to determine the respiratory rhythm and pulse rate with an under-pillow sensor during sleep. The sensor is composed of two fluid-filled polyvinyl tubes set in parallel and sandwiched between two acrylic plates. One end of each tube is hermetically sealed, and the other end is connected to one of two pressure sensors. Inner pressure in each tube therefore changes in accordance with respiratory motion and cardiac beating. By employing the á trous algorithm of wavelet transformation (WT), the respiratory and cardiac cycle can be discriminated from the pressure waveforms. The respiratory rhythm was obtained from the WT 2> scale approximation, and the pulse rate from the sum of WT 2and 2scale details without WT reconstruction after soft-threshold denoising. The algorithm's latency can be set to be minimal and the respiratory rhythm and pulse rate were estimated directly from the extracted respiration and pulse waveforms, respectively. This method has been tested with a total of about 25 h data collected from 13 subjects. By comparing the detection results with those of reference data, the average pulse rate detection sensitivity and positive predictivity were 99.17% and 98.53%, and the respiratory rhythm detection sensitivity and positive predictivity were 95.63% and 95.42%.
本文提出了一种实时、无创且无约束的方法,用于在睡眠期间通过置于枕头下的传感器确定呼吸节律和脉搏率。该传感器由两根平行设置且夹在两块丙烯酸板之间的充液聚乙烯管组成。每根管子的一端密封,另一端连接到两个压力传感器之一。因此,每根管子内的压力会根据呼吸运动和心脏跳动而变化。通过采用小波变换(WT)的à trous算法,可以从压力波形中区分出呼吸周期和心动周期。呼吸节律从WT 2>尺度近似中获得,脉搏率从软阈值去噪后未经WT重建的WT 2和2尺度细节之和中获得。该算法的延迟可以设置为最小,并且分别直接从提取的呼吸和脉搏波形中估计呼吸节律和脉搏率。该方法已用从13名受试者收集的总共约25小时的数据进行了测试。通过将检测结果与参考数据进行比较,平均脉搏率检测灵敏度和阳性预测值分别为99.17%和98.53%,呼吸节律检测灵敏度和阳性预测值分别为95.63%和95.42%。