Paiva R P, Carvalho P, Aubert X, Muehlsteff J, Henriques J, Antunes M
Department of Informatics Engineering, Science and Technology Faculty of the University of Coimbra, Pólo II, Coimbra, Portugal.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:3129-33. doi: 10.1109/IEMBS.2009.5332572.
This paper addresses the estimation of systolic time intervals, namely the pre-ejection period (PEP) and the left ventricular ejection time (LVET), using heart sound. PEP is estimated with a Bayesian approach resorting to the signal's instantaneous amplitude and typical time intervals between atrio-ventricular valve closure and aortic valve opening. As for LVET, aortic valve closure is determined through the analysis of a high-frequency signature of S2. Additionally, LVET has also been estimated from a PPG signal at a peripheral site, for the sake of comparison over a subset of data. We evaluated our algorithms on a set of 658 heartbeats and achieved 10.32 msec average absolute PEP estimation error with 7.3 msec standard deviation and for LVET, 15.8 msec average estimation error with 13.6 msec standard deviation. Current results support our assumption that heart sounds can be applied to detect the onset of the aortic valve movement processes.
本文探讨了利用心音估计收缩期时间间隔，即射血前期（PEP）和左心室射血时间（LVET）的方法。PEP采用贝叶斯方法进行估计，该方法依据信号的瞬时幅度以及房室瓣关闭与主动脉瓣开放之间的典型时间间隔。至于LVET，则通过分析S2的高频特征来确定主动脉瓣关闭。此外，为了在一部分数据上进行比较，还从外周部位的光电容积脉搏波（PPG）信号中估计了LVET。我们在一组658次心跳数据上对算法进行了评估，PEP估计的平均绝对误差为10.32毫秒，标准差为7.3毫秒；LVET的平均估计误差为15.8毫秒，标准差为13.6毫秒。当前结果支持了我们的假设，即心音可用于检测主动脉瓣运动过程的起始。
