Automatic extraction of physiological features from vibro-acoustic heart signals: correlation with echo-doppler

G. Amit, N. Gavriely, J. Lessick, N. Intrator
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引用次数: 12

Abstract

The mechanical processes within the cardiovascular system produce low-frequency vibrations and sounds. These vibro-acoustic signals carry valuable physiological information that can be potentially used for cardiac monitoring. In this work, heart sounds, apical pulse, and arterial pulse signals were simultaneously acquired, along with electrocardiogram and echo-Doppler audio signals. Processing algorithms were developed to extract temporal and morphological feature from the signals. Spectral analysis was used to reconstruct the Doppler sonograms and estimate reference values. A good agreement was observed between systolic and diastolic time intervals estimated by both methods. Strong beat-to-beat correlations were shown both in rest and during pharmacological stress test. The results demonstrate the technological and medical feasibility of using automatic analysis of vibro-acoustic heart signals for continuous non-invasive monitoring of cardiac functionality
心脏振动声信号生理特征的自动提取:与回声多普勒的相关性
心血管系统内的机械过程产生低频振动和声音。这些振动声信号携带有价值的生理信息,可以潜在地用于心脏监测。在这项工作中,心音、心尖脉冲和动脉脉冲信号,以及心电图和回声多普勒音频信号同时被采集。开发了从信号中提取时间和形态特征的处理算法。光谱分析用于重建多普勒超声图和估计参考值。两种方法估计的收缩期和舒张期时间间隔有很好的一致性。在休息和药理学压力测试中均显示出强烈的搏动相关性。结果表明,利用振动声心脏信号自动分析进行心脏功能的连续无创监测在技术和医学上是可行的
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