心音

例如，确定心电图中QRS波的复杂性、心律不齐以及分析异常心音等往往很有必要的。

Determine , for example , the complexity of the QRS waves in ecg , arrhythmia , and analysis of abnormal heart sounds is often necessary .

目的：研究第三（S3）第四（S4）心音在临床上的意义。

Objective : To find out the clinical significance of the third ( S3 ) and fourth ( S4 ) heart sounds .

基于定点DSP芯片实现的心音辅助诊断仪

A Heart Sound Accessorial Diagnosis Instrument Based On Fixed-DSP

心音信号的非高斯AR模型双谱分析

Bispectral analysis of heart sound signals via non-Gaussian AR model

非高斯AR模型及其在心音信号分析中的应用

Non-Gaussian AR Model and Applications in the Analysis of Heart Sound Signals

相对于临床上广泛使用的ECG信号，心音信号具有自身的特点和优势。

Relative to ECG used universally in the clinic , heart sound signal possesses itself characteristics and advantages .

脑血管阻力（R）通过计算获得，心音传感器放置在心前区，ECG记录标准Ⅱ导联。

A heart sound transducer was placed on the precordium . A standard II lead of ECG was used to record .

医院ICU病房的心音监测系统

The heart sound monitoring system for ICU wards

基于规则平均Shannon能量变换的心音信号包络波形提取；

Secondly , heart sound envelope is extracted by using normalized average Shannon energy transform ;

本文利用高阶谱分析方法，提出以非高斯AR模型对心音信号进行参数化双谱估计。

In the paper , non-Gaussian parametric model is proposed for parametric bispectral estimation of heart sound signals based on higher-order spectra .

本心音分析系统是基于Windows操作系统、以VC++6.0为平台进行开发的。

The analysis system is based on the windows operating system and is developed by Visual C + + 6.0 . The system is made up of four modules functionally .

基于心音传感阵列ICA信号处理的冠心病诊断的研究

The Research of Diagnosis of Coronary Artery Disease Based on the Application of Independent Component Analysis to Heart Sounds Sensor Array

基于WPT分层和独立子波函数的单路心音混合信号BSS新方法

A BSS Method of Single-channel Signal Based on WPT Layered Technique and Independent Sub-band Functions

针对此本文提出了基于Hilbert-HUANGTRANSFORM（HHT）的心音信号的分析方法，对冠心病患者的心音信号进行了分析。

A novel method based on Hilbert-Huang Transform ( HHT ) is introduced . The heart sound signal of coronary artery disease is analyzed .

心音图有下列特点：（1）心房音（Sa）与房扑波（F）密切相关，F&Sa间期为0.19秒；

The features of phonocardiogram were as follows : ( 1 ) There is a close relationship between Sa and F wave . F-Sa interval is 0.19 second .

Hilbert谱及其边界谱在时域以及频域以较高的分辨率表征了心音信号的时频变化特性，揭示了冠心病患者心音信号的病理特征；

The Hilbert spectrum and marginal spectrum provide high-resolution time-varying characteristic of heart sound signal , the result shows the clinical characteristic of CAD .

方法：采用声卡并结合Matlab软件实现对胎儿心音信号的采集，并分别运用自相关算法和自适应算法对信号进行分析。

Meth - ods : The sound card and Matlab were used to acquire fetal heart sound and at the same time autocorrelation analysis and adaptive filter algorithm were used respectively to analyze it .

利用GPRS网络覆盖广、安全性高、数据传输速率较高的特性可实现心音信号的远程传输和无缝接入。

Heart sound teletransmission and seamless access can be implemented based on characteristics of GPRS such as wide network coverage , high security , wide bandwidth and so on .

基于心音包络信号的第一心音S1、第二心音S2波峰提取和定位；

Thirdly , the peaks of S1 and S2 are picked up and detected based on the extracted envelope of heart sound signal ;

基于DSP的心音采集系统，不仅能够实现心率检测，同时又可做为一套完整的数字电子听诊系统。

Phonocardiogram ( PCG ) detection system based on Digital Signal Processor ( DSP ), not only is applied for heart rate detection , but also can be used as an integrated digital electronic auscultation system .

本文的算法对S1与S2识别的准确率达到了86%，其中对于正常心音信号的识别准确率更是达到了100%。

The accuracy of recognition was up to 86 % , specially , for the normal heart sound , the accuracy reached 100 % .

其次，对心音信号的非高斯AR模型的定阶进行讨论，提出采用双谱互相关法估计心音信号的模型阶次。

The method for AR model order selection based on bispectral cross correlation was proposed and applied to estimate the AR model order of the heart sound signals for parametric bispectral estimation .

一种基于Choi-Williams分布的心音信号检测方法

A detection method of heart sound signals using Choi Williams distribution

最后，利用DSP专用汇编语言编写心音信号处理程序，程序主要分为三个模块：小波分析模块，数学形态学模块和幅值提取模块。

At last , this paper uses special assemble language of DSP to program the heart sound signals . The procedure has three modules : the wavelet module , the mathematic morphology module , the amplitude extraction module .

有效提取心音包络对于检测S1、S2，分离杂音进而判断心脏病类型和严重程度具有重要意义。

The efficient extraction of the heart sound envelope can significantly facilitate detecting S1 , S2 , separating murmurs and therefore determining the severity of cardiac disease .

本文用一种全新的时频分析方法：Hilbert-Huang变换（HHT），对30例心音数据进行心音分析实验.实验结果表明：HHT方法可以有效的分析心音信号；

In this paper , a new method using the Hilbert-Huang Transform ( HHT ) was used to decompose S1 into a series of time-frequency atoms .

该部分主要介绍了利用计算机中的声卡装置然后结合Matlab语言将超声探头获取的胎儿心音信号输入到计算机中，以方便进行进一步的分析和处理。

This part mainly introduces a method of how to utilize the sound card and combining Matlab language to input the fetal heart sound signal into the computers . It is in order to carry on further analysis and treatment .

介绍了SVM分类原理，并将其应用于心音正常和异常的分类诊断上。本文采用的80例正常心音的识别率达到98.9%，80例异常心音也获得了92.3%的识别率。

After the principles of SVM is described , it is used to the classification of normal and abnormal heart sound diagnosis with correct classification rate of 98.9 % for normal and 92.3 % for abnormal .

目的本文介绍一种在心音图（PCG）中定位第一心音（S1）和第二心音（S2）的算法。

Objective An algorithm located the first sound ( S 1 ) and the second sound ( S 2 ) on phonocardiogram ( PCG ) was introduced .

本文提出一种基于数学形态学的心音包络提取方法，并在提取出的心音包络信号中识别第一心音（S1）与第二心音（S2）。

This study put forward a heart sound envelope detection method based on the mathematical morphology . Then on the heart sound envelope , S1 and S2 were recognized .