The Design Of R-wave ECG Signal Recognition System

At the present, cardiovascular disease is one of the most common chronic disease, dueto its high death rate, it has been became a worldwide public health problem. The ECGautomatic analysis and identification of research and development provide a very highclinical value for daily monitoring, diagnostics towards of heart disease. Because of theweak ECG signal is nonlinearity and easily interfered by human body, so the difficulty ofrecognition diagnosis is increasing. As a result, improving the accuracy of ECG signaldetection system is a prerequisite for diagnosis of cardiovascular disease. Therefore, weoften pre-process the signal before analyzing,which affect directly the signal analysis anddiagnosis. In the diagnosis of signal, it is particularly important that the detection of QRSwave in ECG diagnosis can provide a lot of useful information for diagnosis and assessmentin ECG automatic diagnosis technology. We can locate other wave features more preciselythrough locating R-wave accurately. Therefore, the parameter extraction of r-wave signalsfor ECG analysis is particularly important，it is a basis to distinguish normal rhythm andpathological rhythm.This thesis mainly focuses on the remote ECG monitoring system. The key technologyis how to deal with the ECG noise suppression preprocessing and R-wave detection and letthem can be realized in MATLAB software in simulation.For the ECG signal preprocessing algorithm research: this paper studied on the ellipticfilter with DB4lifting programme combining algorithm for denoising of ECG signalpretreatment. The wavelet transform of wavelet coefficients are using the method ofweighted threshold for processing. Experimental data showed that this paper puts forwardan efficient structure to remove efficiently interference from ECG signal. Furthermore, it’sbetter to keep details characteristics and provide more effective data for the subsequenttesting. This article was given the feasibility design of the ECG signal preprocessingalgorithm for hardware implementation scheme, which based on the theory of elliptic filterand lifting wavelet structure，and which was also verified that the algorithm reduced theamount of calculation and saved the hardware space.For the characteristics of R-wave detection algorithm research: this article improved Rwave of ECG data detection algorithm for inverted R wave, contains motion artifact whichbased on wavelet transform algorithm. Through the analysis of R-wave on with Hilbert,wavelet transform on feature points. The bi-orthogonal B-spline wavelet as wavelets filterfor the R wave detection algorithm, through the wavelet multiscale analysis, in the end, Itwas selected the third scale to by looking for modulus maxima to locate R-waves in ECGsignal. Then the wavelet coefficient deals with the Hilbert transform which based on Mallatalgorithm, the wavelet multiscale analysis.This paper also improved the detection rate, especially finishing the improving the detection algorithm and reduced the probability ofdis-detecting and leak-detecting.For the performance analysis of research: this paper mainly studied R-wave detection,which base on MATLAB software simulation and data contract. This article chose therepresentative data from the MIT/BIH ECG database and carried out to verify the detectionalgorithm base on waveform simulation, and gave the feasibility analysis. At the same time,this paper completed the design of the automatic identification of R wave analysis systemwhich based on the Visual Studio.net2012software development platform and C#.netprogramming language.