Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand.
GIGA Cardiovascular Science, University of Liège, Liège, Belgium.
J Clin Monit Comput. 2021 Feb;35(1):79-88. doi: 10.1007/s10877-020-00473-3. Epub 2020 Feb 11.
Identification of end systole is often necessary when studying events specific to systole or diastole, for example, models that estimate cardiac function and systolic time intervals like left ventricular ejection duration. In proximal arterial pressure waveforms, such as from the aorta, the dicrotic notch marks this transition from systole to diastole. However, distal arterial pressure measures are more common in a clinical setting, typically containing no dicrotic notch. This study defines a new end systole detection algorithm, for dicrotic notch-less arterial waveforms. The new algorithm utilises the beta distribution probability density function as a weighting function, which is adaptive based on previous heartbeats end systole locations. Its accuracy is compared with an existing end systole estimation method, on dicrotic notch-less distal pressure waveforms. Because there are no dicrotic notches defining end systole, validating which method performed better is more difficult. Thus, a validation method is developed using dicrotic notch locations from simultaneously measured aortic pressure, forward projected by pulse transit time (PTT) to the more distal pressure signal. Systolic durations, estimated by each of the end systole estimates, are then compared to the validation systolic duration provided by the PTT based end systole point. Data comes from ten pigs, across two protocols testing the algorithms under different hemodynamic states. The resulting mean difference ± limits of agreement between measured and estimated systolic duration, of [Formula: see text] versus [Formula: see text], for the new and existing algorithms respectively, indicate the new algorithms superiority.
当研究特定于心室收缩或舒张期的事件时，例如估计心脏功能和收缩时间间隔（如左心室射血时间）的模型，通常需要识别心室收缩末期。在近端动脉压力波形中，如主动脉压力波形，重搏切迹标记着从收缩期到舒张期的转变。然而，在临床环境中更常见的是远端动脉压力测量，通常没有重搏切迹。本研究定义了一种新的无重搏切迹动脉波形的心室收缩末期检测算法。新算法利用贝塔分布概率密度函数作为加权函数，根据前几个心跳的心室收缩末期位置进行自适应调整。将其准确性与现有的心室收缩末期估计方法进行比较，该方法用于无重搏切迹的远端压力波形。由于没有重搏切迹来定义心室收缩末期，因此更难确定哪种方法表现更好。因此，开发了一种使用通过脉搏传导时间（PTT）向前投影到更远端压力信号的主动脉压力中的重搏切迹位置进行验证的方法。然后，通过 PTT 基于心室收缩末期点提供的验证收缩期持续时间，比较每个心室收缩末期估计值估计的收缩期持续时间。数据来自 10 头猪，在两种不同的血流动力学状态下测试算法的协议中。新算法和现有算法的测量和估计收缩期持续时间之间的平均差异±一致性界限分别为[公式：见正文]和[公式：见正文]，表明新算法具有优越性。
