一项利用独立成分分析技术进行心音和肺音分离的研究。

A study of heart sound and lung sound separation by independent component analysis technique.

作者信息

Chien Jen-Chien, Huang Ming-Chuan, Lin Yue-Der, Chong Fok-ching

机构信息

Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, ROC.

出版信息

Conf Proc IEEE Eng Med Biol Soc. 2006;2006:5708-11. doi: 10.1109/IEMBS.2006.260223.

DOI:10.1109/IEMBS.2006.260223

PMID:17945913

Abstract

In the hospital, using percussion and auscultation are the most common ways for physical examination. Recently, in order to develop tele-medicine and home care system and to assist physician getting better auscultation results; electric stethoscope and computer analysis have become an inevitable trend. However, two important physical signals heart sound and lung sound recorded from chest overlap on spectrum chart. Therefore, in order to reduce human factor (ex. misplace or untrained of using) and minimize correlated effect in computer analysis; it's necessary for separated heart sound and lung sound. Independent component analysis can divide these sounds efficiency. In this paper, we use two microphones to collect signals from left and right chest. We have successfully divide heart and lung sounds by fast ICA algorithm. Therefore, it can assist physician examine and also using on tele-medicine and home care by this way.

摘要

在医院里，叩诊和听诊是体格检查最常用的方法。近来，为了发展远程医疗和家庭护理系统，并帮助医生获得更好的听诊结果，电子听诊器和计算机分析已成为必然趋势。然而，从胸部记录的两个重要生理信号心音和肺音在频谱图上相互重叠。因此，为了减少人为因素（如放置错误或使用未经培训）并在计算机分析中最小化相关影响，分离心音和肺音是必要的。独立成分分析能够有效地分离这些声音。在本文中，我们使用两个麦克风从左右胸部采集信号。我们已通过快速独立成分分析算法成功分离了心音和肺音。因此，它可以辅助医生进行检查，并且通过这种方式还可用于远程医疗和家庭护理。