Cernat Roxana A, Ciorecan Silvia I, Ungureanu Constantin, Arends Johan, Strungaru Rodica, Ungureanu G Mihaela
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:5977-80. doi: 10.1109/EMBC.2015.7319753.
The respiratory rate is a vital parameter that can provide valuable information about the health condition of a patient. The extraction of respiratory information from photoplethysmographic signal (PPG) was actually encouraged by the reported results, our main goal being to obtain accurate respiratory rate estimation from the PPG signal. We developed a fusion algorithm that identifies the best derived respiratory signals, from which is possible to extract the respiratory rate; based on these, a global respiratory rate is computed using the proposed fusion algorithm. The algorithm is qualitatively tested on real PPG signals recorded by an acquisition system we implemented, using a reflection pulse oximeter sensor. Its performance is also statistically evaluated using benchmark dataset publically available from CapnoBase.Org.
呼吸频率是一个重要参数,可提供有关患者健康状况的有价值信息。从光电容积脉搏波信号(PPG)中提取呼吸信息实际上受到了已报道结果的推动,我们的主要目标是从PPG信号中获得准确的呼吸频率估计。我们开发了一种融合算法,该算法可识别最佳的派生呼吸信号,从中可以提取呼吸频率;基于这些信号,使用所提出的融合算法计算全局呼吸频率。该算法在我们使用反射式脉搏血氧仪传感器实现的采集系统记录的真实PPG信号上进行了定性测试。其性能还使用从CapnoBase.Org公开获得的基准数据集进行了统计评估。