The Study Of Cardiac Function Detection System Base On Pcg And Ecg

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 moduleAccording 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.