基于心音和心电的心功能检测系统研究
摘要
心血管疾病已成为导致人类死亡最主要的原因,是世界范围内的临床医学和人类社会负担。在临床方面:心脏性猝死、孕产妇心脏健康问题,麻醉安全问题与心脏都有着直接或间接的联系。目前,临床关于心脏性猝死的预警、心脏监护室和危重病人监护、麻醉安全监测项目中都没有对心脏储备指标的监测,忽略了从心力、心律、心率等几个方面同时观察研究。因此,开展基于“心音和心电综合分析”的研究具有重要的学术意义和实用价值。
本文在总结前人工作的基础上,围绕基于心音和心电的心功能检测系统研究进行,完成的主要研究工作如下:
1、完成一种基于心音和心电的心功能检测系统原型设计,进而提出一种基于USB Hub的模块化医疗仪器构建方法。该方法是:各功能电路采用模块化设计,各模块中独立采用一个微处理器,具有独立的AD转换和USB通信控制功能;各功能模块通过USB总线与具有电气安全隔离功能的USB Hub模块连接;USB Hub模块通过USB总线实现与基于PC的软件平台连接,组成完整的医疗仪器系统。基于心音和心电的心功能检测系统包括:多生理参数信号硬件采集模块、USB Hub模块、电源模块、计算机处理系统和输出设备。其中,多生理参数信号硬件采集和处理模块包括:心音信号采集模块、心电信号采集模块和无创血压采集模块。
系统硬件设计中采用分频段进行心音信号检测,USB Hub控制器采用美国TI公司的全速通用串行总线集线器TUSB2036实现,采用恩智浦半导体公司(NXP Semiconductors)推出的PRTR5V0U2X为USB2端口提供ESD保护,采用一体化的USB总线隔离器ADuM4160实现USB总线的医疗级电气安全隔离,采用模块化50Hz陷波器MXT050实现50Hz陷波。系统软件设计包括:启动界面模块、数据采集模块、数据显示模块、数据处理模块、数据库管理模块、诊断报警模块。在数据处理模块设计中采用LabVIEW与MATLAB混合编程技术,通过希尔伯特-黄变换对心音进行定位分析,提取心脏储备指标D/S、S1/S2,S1和S2倒置等,在心音信号处理模块中还设计了FFT频谱分析程序,可对所有WAV格式的心音文件进行时频域分析;通过基于Maxican hat小波变换算法实现QRS波检测,采用双阈值法,平面几何方法等多种判别策略对P波和T波的形态进行判断,实现心电信号的识别和相关指标的提取。
2、初步提出一种基于“心音和心电综合分析”的心功能无创检测方法。根据预防医学、混沌医学和稳态理论,结合无脉性电活动的特点提出了一种基于心音和心电的心功能无创检测方法。该方法指的是同步采集心音信号、心电信号、手臂动脉脉搏波信号;获得同步的心音图、心电图;提取心脏储备指标、心电图指标、心音图和心电图综合指标、无创血压指标;从心率变异性,心肌变力性、变时性和变传导性等几个方面全面观察心脏功能状态。该方法可为探明心脏性猝死机制的最初环节和找到猝死的早期线索,提供一种新思路;有益于及早发现孕产妇围生期的心脏功能异常,为临床采取保障妇幼健康的措施提供新依据;为围麻醉期和围手术期的临床实践补充具有实用价值的新指标,减少麻醉事故。
Cardiovascular diseases have been the main cause of death and a burden to clinical medicine as well as human society all over the world.
In clinic, cardiac function is directly or indirectly related to Sudden Cardiac Death (SCD), heart health of pregnant women and parturients as well as anesthesia safety. At present, the indicators on early warning of SCD, management of cardiac diseases during pregnancy, monitoring of anesthesia safety have overlooked simultaneous study on the cardiac contractility, cardiac rhythm, and heart rate. For this reason, to develop cardiac function detection system based on PCG and ECG is of great significance both academically and practically.
This thesis,based on previous studies, focuses on cardiac function detection system based on PCG and ECG signal. Accomplished works are as follows:
First of all, the system prototype based on PCG and ECG signal is completed and a USB Hub-based constructing method of modular medical equipment is put forward. In this method, every functional circuit is designed as a module and each module deploys a microprocessor independently, with ADC and USB function controller. In the system, the functional module employs USB Hub to implement data communication to PC-based software so as to construct a complete system of medical equipment.
The cardiac function detection system based on PCG and ECG , which is capable of carrying out simultaneous measurement of PCG,EEG and pulse wave signal, consists of multiple physiological parameters signal acquisition module, USB Hub module, power module, PC-based software and output devices. Among which, the multiple physiological parameters signal acquisition module includes Heart sound signal acquisition module, ECG acquisition module and non-invasive blood pressure acquisition module
According to the system functional requirement, this thesis adopts sub-band for heart sound detection, (ultra-low frequency circuits, very low frequency circuits, low-frequency circuit, medium frequency circuit, high frequency circuit), with ADuM4160 to implement the medical grade isolation of USB bus, and modular 50Hz notch filter MXT050 to achieve 50Hz notch. The system software modular design includes startup program interface module, data acquisition module, data display module, data processing and analysis module, database module, diagnostic and alarm module. In the data processing and analysis module, which is based on LabVIEW and MATLAB mixed programming method, this thesis adopts Hilbert-Huang Transform algorithm for detection of S1 and S2 components of heart sound so as to extract cardiac reserve indicators. And the ECG signals are transformed by using Mexican-hat wavelet. At the same time, the Q wave, R wave and the QRS jumping-ending point are detected, using the plane geometry method. Furthermore, according to the complexity and variety of the form of P wave and T wave, various distinguish method, such as slope and amplitude ratio, are used to distinguish the form of P waves and T wave so as to extract indicators of ECG. Additionally, the time–frequency spectral analyzing program is designed to implement the analysis of WAV format heart sound files.
In particular, according to preventive medicine, medical and stable chaos theory, combined with the features of pulseless electrical activity, this thesis preliminarily devises a non-invasive cardiac function method based on comprehensive analysis of PCG and ECG. The method is to simultaneously collect PCG, EEG and pulse wave signal and extract cardiac reserve indicators, ECG indicators, comprehensive indicators of PCG and ECG and non-invasive blood pressure indicators. Finally,a comprehensive observation is carried out on the cardiac function from the aspects of heart rate variability, cardiac contractility variability and cardiac contractility change trend etc. Hopefully, this method will shed a new light on exploring pre-symptoms of SCD, benefiting early detection of perinatal period cardiac dysfunction of pregnant women along with parturients and adding new cardiac function indicators with practical value for clinical perioperative anesthesia.
本文在总结前人工作的基础上,围绕基于心音和心电的心功能检测系统研究进行,完成的主要研究工作如下:
1、完成一种基于心音和心电的心功能检测系统原型设计,进而提出一种基于USB Hub的模块化医疗仪器构建方法。该方法是:各功能电路采用模块化设计,各模块中独立采用一个微处理器,具有独立的AD转换和USB通信控制功能;各功能模块通过USB总线与具有电气安全隔离功能的USB Hub模块连接;USB Hub模块通过USB总线实现与基于PC的软件平台连接,组成完整的医疗仪器系统。基于心音和心电的心功能检测系统包括:多生理参数信号硬件采集模块、USB Hub模块、电源模块、计算机处理系统和输出设备。其中,多生理参数信号硬件采集和处理模块包括:心音信号采集模块、心电信号采集模块和无创血压采集模块。
系统硬件设计中采用分频段进行心音信号检测,USB Hub控制器采用美国TI公司的全速通用串行总线集线器TUSB2036实现,采用恩智浦半导体公司(NXP Semiconductors)推出的PRTR5V0U2X为USB2端口提供ESD保护,采用一体化的USB总线隔离器ADuM4160实现USB总线的医疗级电气安全隔离,采用模块化50Hz陷波器MXT050实现50Hz陷波。系统软件设计包括:启动界面模块、数据采集模块、数据显示模块、数据处理模块、数据库管理模块、诊断报警模块。在数据处理模块设计中采用LabVIEW与MATLAB混合编程技术,通过希尔伯特-黄变换对心音进行定位分析,提取心脏储备指标D/S、S1/S2,S1和S2倒置等,在心音信号处理模块中还设计了FFT频谱分析程序,可对所有WAV格式的心音文件进行时频域分析;通过基于Maxican hat小波变换算法实现QRS波检测,采用双阈值法,平面几何方法等多种判别策略对P波和T波的形态进行判断,实现心电信号的识别和相关指标的提取。
2、初步提出一种基于“心音和心电综合分析”的心功能无创检测方法。根据预防医学、混沌医学和稳态理论,结合无脉性电活动的特点提出了一种基于心音和心电的心功能无创检测方法。该方法指的是同步采集心音信号、心电信号、手臂动脉脉搏波信号;获得同步的心音图、心电图;提取心脏储备指标、心电图指标、心音图和心电图综合指标、无创血压指标;从心率变异性,心肌变力性、变时性和变传导性等几个方面全面观察心脏功能状态。该方法可为探明心脏性猝死机制的最初环节和找到猝死的早期线索,提供一种新思路;有益于及早发现孕产妇围生期的心脏功能异常,为临床采取保障妇幼健康的措施提供新依据;为围麻醉期和围手术期的临床实践补充具有实用价值的新指标,减少麻醉事故。
Cardiovascular diseases have been the main cause of death and a burden to clinical medicine as well as human society all over the world.
In clinic, cardiac function is directly or indirectly related to Sudden Cardiac Death (SCD), heart health of pregnant women and parturients as well as anesthesia safety. At present, the indicators on early warning of SCD, management of cardiac diseases during pregnancy, monitoring of anesthesia safety have overlooked simultaneous study on the cardiac contractility, cardiac rhythm, and heart rate. For this reason, to develop cardiac function detection system based on PCG and ECG is of great significance both academically and practically.
This thesis,based on previous studies, focuses on cardiac function detection system based on PCG and ECG signal. Accomplished works are as follows:
First of all, the system prototype based on PCG and ECG signal is completed and a USB Hub-based constructing method of modular medical equipment is put forward. In this method, every functional circuit is designed as a module and each module deploys a microprocessor independently, with ADC and USB function controller. In the system, the functional module employs USB Hub to implement data communication to PC-based software so as to construct a complete system of medical equipment.
The cardiac function detection system based on PCG and ECG , which is capable of carrying out simultaneous measurement of PCG,EEG and pulse wave signal, consists of multiple physiological parameters signal acquisition module, USB Hub module, power module, PC-based software and output devices. Among which, the multiple physiological parameters signal acquisition module includes Heart sound signal acquisition module, ECG acquisition module and non-invasive blood pressure acquisition module
According to the system functional requirement, this thesis adopts sub-band for heart sound detection, (ultra-low frequency circuits, very low frequency circuits, low-frequency circuit, medium frequency circuit, high frequency circuit), with ADuM4160 to implement the medical grade isolation of USB bus, and modular 50Hz notch filter MXT050 to achieve 50Hz notch. The system software modular design includes startup program interface module, data acquisition module, data display module, data processing and analysis module, database module, diagnostic and alarm module. In the data processing and analysis module, which is based on LabVIEW and MATLAB mixed programming method, this thesis adopts Hilbert-Huang Transform algorithm for detection of S1 and S2 components of heart sound so as to extract cardiac reserve indicators. And the ECG signals are transformed by using Mexican-hat wavelet. At the same time, the Q wave, R wave and the QRS jumping-ending point are detected, using the plane geometry method. Furthermore, according to the complexity and variety of the form of P wave and T wave, various distinguish method, such as slope and amplitude ratio, are used to distinguish the form of P waves and T wave so as to extract indicators of ECG. Additionally, the time–frequency spectral analyzing program is designed to implement the analysis of WAV format heart sound files.
In particular, according to preventive medicine, medical and stable chaos theory, combined with the features of pulseless electrical activity, this thesis preliminarily devises a non-invasive cardiac function method based on comprehensive analysis of PCG and ECG. The method is to simultaneously collect PCG, EEG and pulse wave signal and extract cardiac reserve indicators, ECG indicators, comprehensive indicators of PCG and ECG and non-invasive blood pressure indicators. Finally,a comprehensive observation is carried out on the cardiac function from the aspects of heart rate variability, cardiac contractility variability and cardiac contractility change trend etc. Hopefully, this method will shed a new light on exploring pre-symptoms of SCD, benefiting early detection of perinatal period cardiac dysfunction of pregnant women along with parturients and adding new cardiac function indicators with practical value for clinical perioperative anesthesia.
引文
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