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采用三阶归一化平均 Shannon 能量包络算法检测和定位 S 和 S2 心音。

Detection and localization of S and S heart sounds by 3rd order normalized average Shannon energy envelope algorithm.

机构信息

Department of Electronics and Communication Engineering, National Institute of Technology (NIT), Patna, India.

Department of Physics, Patna Women's College, Patna, India.

出版信息

Proc Inst Mech Eng H. 2021 Jun;235(6):615-624. doi: 10.1177/0954411921998108. Epub 2021 Mar 30.

Abstract

Adults born after 1970s are more prone to cardiovascular diseases. Death rate percentage is quite high due to heart related diseases. Therefore, there is necessity to enquire the problem or detection of heart diseases earlier for their proper treatment. As, Valvular heart disease, that is, stenosis and regurgitation of heart valve, are also a major cause of heart failure; which can be diagnosed at early-stage by detection and analysis of heart sound signal, that is, HS signal. In this proposed work, an attempt has been made to detect and localize the major heart sounds, that is, S and S. The work in this article consists of three parts. Firstly, self-acquisition of Phonocardiogram (PCG) and Electrocardiogram (ECG) signal through a self-assembled, data-acquisition set-up. The Phonocardiogram (PCG) signal is acquired from all the four auscultation areas, that is, Aortic, Pulmonic, Tricuspid and Mitral on human chest, using electronic stethoscope. Secondly, the major heart sounds, that is, S and Sare detected using 3rd Order Normalized Average Shannon energy Envelope (3rd Order NASE) Algorithm. Further, an auto-thresholding has been used to localize time gates of S and S and that of R-peaks of simultaneously recorded ECG signal. In third part; the successful detection rate of S and S, from self-acquired PCG signals is computed and compared. A total of 280 samples from same subjects as well as from different subjects (of age group 15-30 years) have been taken in which 70 samples are taken from each auscultation area of human chest. Moreover, simultaneous recording of ECG has also been performed. It was analyzed and observed that detection and localization of S and S found 74% successful for the self-acquired heart sound signal, if the heart sound data is recorded from pulmonic position of Human chest. The success rate could be much higher, if standard data base of heart sound signal would be used for the same analysis method. The, remaining three auscultations areas, that is, Aortic, Tricuspid, and Mitral have smaller success rate of detection of S and S from self-acquired PCG signals. So, this work justifies that the Pulmonic position of heart is most suitable auscultation area for acquiring PCG signal for detection and localization of S and S much accurately and for analysis purpose.

摘要

20 世纪 70 年代以后出生的成年人更容易患心血管疾病。由于与心脏有关的疾病,死亡率相当高。因此,有必要尽早询问或发现心脏病,以便进行适当的治疗。瓣膜性心脏病,即心脏瓣膜狭窄和反流,也是心力衰竭的主要原因;通过检测和分析心音信号,即 HS 信号,可以在早期诊断。在这项工作中,尝试检测和定位主要心音,即 S 和 S。本文的工作分为三部分。首先,通过自组装的数据采集装置,自行采集心音图(PCG)和心电图(ECG)信号。使用电子听诊器从人体胸部的四个听诊区(主动脉瓣、肺动脉瓣、三尖瓣和二尖瓣)采集心音图(PCG)信号。其次,使用三阶归一化平均 Shannon 能量包络(3rd Order NASE)算法检测主要心音,即 S 和 S。进一步,使用自动阈值定位 S 和 S 的时间门和同时记录的 ECG 信号的 R 峰。在第三部分;计算并比较了从自行采集的 PCG 信号中成功检测到 S 和 S 的比率。总共从相同的受试者和不同的受试者(年龄组 15-30 岁)中采集了 280 个样本,其中从人体胸部的每个听诊区采集 70 个样本。此外,还同时进行了心电图记录。分析和观察发现,如果从人体胸部的肺动脉瓣位置记录心音数据,那么自采集心音信号的 S 和 S 检测和定位的成功率为 74%。如果使用心音信号的标准数据库进行相同的分析方法,成功率可能会更高。其余三个听诊区,即主动脉瓣、三尖瓣和二尖瓣,从自采集的 PCG 信号中检测到 S 和 S 的成功率较低。因此,这项工作证明,心脏的肺动脉瓣位置最适合采集 PCG 信号,以便更准确地检测和定位 S 和 S,并进行分析。

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