Kumar D, Carvalho P, Antunes M, Henriques J
Department of Informatics Engineering of the University of Coimbra, Polo-II, Coimbra, Portugal.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:3119-23. doi: 10.1109/IEMBS.2009.5332569.
Heart sound is a valuable biosignal for early detection of a large set of cardiac diseases. Ambient and physiological noise interference is one of the most usual and high probable incidents during heart sound acquisition. It may change the prominent and crucial characteristics of heart sound which may possess important information for heart disease diagnosis. In this paper, we propose a new method to detect ambient and internal body noises in heart sounds. The algorithm utilizes physiologically inspired periodicity/semi-periodicity criteria. A small segment of clean heart sound exhibiting periodicity in the time and in the frequency domain is first detected. The sound segment is used as a template to detect uncontaminated heart sounds during recording. The technique has been tested on the heart sounds contaminated with several types of noises, recorded from 68 different subjects. Average sensitivity of 95.13% and specificity of 98.65% for non-cardiac sound detection were achieved.
心音是用于早期检测大量心脏疾病的重要生物信号。在获取心音过程中，环境噪声和生理噪声干扰是最常见且很可能发生的情况之一。它可能会改变心音的显著和关键特征，而这些特征可能包含心脏病诊断的重要信息。在本文中，我们提出了一种检测心音中环境噪声和体内噪声的新方法。该算法利用了受生理启发的周期性/半周期性标准。首先检测一小段在时域和频域均呈现周期性的纯净心音。该声音片段用作模板，以在记录过程中检测未受污染的心音。该技术已在从68名不同受试者记录的、被多种类型噪声污染的心音上进行了测试。非心音检测的平均灵敏度达到95.13%，特异性达到98.65%。
