Center for Informatics and Systems of the University of Coimbra, Pólo II, Coimbra, Portugal.
Physiol Meas. 2012 Feb;33(2):177-94. doi: 10.1088/0967-3334/33/2/177. Epub 2012 Jan 19.
Systolic time intervals are highly correlated to fundamental cardiac functions. Several studies have shown that these measurements have significant diagnostic and prognostic value in heart failure condition and are adequate for long-term patient follow-up and disease management. In this paper, we investigate the feasibility of using heart sound (HS) to accurately measure the opening and closing moments of the aortic heart valve. These moments are crucial to define the main systolic timings of the heart cycle, i.e. pre-ejection period (PEP) and left ventricular ejection time (LVET). We introduce an algorithm for automatic extraction of PEP and LVET using HS and electrocardiogram. PEP is estimated with a Bayesian approach using the signal's instantaneous amplitude and patient-specific time intervals between atrio-ventricular valve closure and aortic valve opening. As for LVET, since the aortic valve closure corresponds to the start of the S2 HS component, we base LVET estimation on the detection of the S2 onset. A comparative assessment of the main systolic time intervals is performed using synchronous signal acquisitions of the current gold standard in cardiac time-interval measurement, i.e. echocardiography, and HS. The algorithms were evaluated on a healthy population, as well as on a group of subjects with different cardiovascular diseases (CVD). In the healthy group, from a set of 942 heartbeats, the proposed algorithm achieved 7.66 ± 5.92 ms absolute PEP estimation error. For LVET, the absolute estimation error was 11.39 ± 8.98 ms. For the CVD population, 404 beats were used, leading to 11.86 ± 8.30 and 17.51 ± 17.21 ms absolute PEP and LVET errors, respectively. The results achieved in this study suggest that HS can be used to accurately estimate LVET and PEP.
心音(HS)可用于精确测量主动脉瓣的开启和关闭时刻。这些时刻对于定义心脏周期的主要收缩时间至关重要,即射血前期(PEP)和左心室射血时间(LVET)。我们引入了一种使用 HS 和心电图自动提取 PEP 和 LVET 的算法。PEP 是使用信号的瞬时幅度和房室瓣关闭与主动脉瓣开放之间的患者特定时间间隔,通过贝叶斯方法进行估计的。至于 LVET,由于主动脉瓣关闭对应于 S2 HS 分量的开始,因此我们基于 S2 起始的检测来估计 LVET。使用当前心脏时间间隔测量的金标准,即超声心动图和 HS 的同步信号采集,对主要收缩时间间隔进行了比较评估。该算法在健康人群以及患有不同心血管疾病(CVD)的人群中进行了评估。在健康组中,从 942 次心跳中,提出的算法实现了 7.66 ± 5.92 ms 的 PEP 绝对估计误差。对于 LVET,绝对估计误差为 11.39 ± 8.98 ms。对于 CVD 人群,使用了 404 次心跳,导致 PEP 和 LVET 的绝对误差分别为 11.86 ± 8.30 和 17.51 ± 17.21 ms。本研究的结果表明,心音可以用于准确估计 LVET 和 PEP。