Ecg Signal Filtering And QRS Wave Locating

Automatic electrocardiogram (ECG) signal analysis is a hot spot in the signalprocessing researching field, its exact realization will greatly promote thedevelopment of the medical profession and raise people’s health level, additionally, itwill also be a major application breakthrough of modern signal processing technologyin medical field. The researching text of the automatic ECG signal analysis system isextensive. Swiftly and accurately positioning the QRS wave group、P wave、T waveis a key step in the system, and effectively filtering the ECG noises is the pre-requisiteof accurately detecting each characteristic wave. So far, much defections andshortcomings still exist in existed signal filtering methods and characteristic wavelocating methods. As for this situation, this paper does the research in the two aspectsof “ECG signal preprocessing” and “QRS wave locating”.Signal filtering: the ECG signal is weak, thus easy to be affected by the outsideenvironment and it is often mixed with EMG interference、baseline drift、powerfrequency interference. The paper focuses on designing the digital filter of eliminatingthe50Hz interference signal. Because of the practical ECG signal processingrequirement, wavelet transformation method and Levkov filtering method arecombined to filter the50Hz power frequency signal in the signal that needed toprocess.QRS wave locating: characteristic wave locating serves as the base of ECGsignal analyzing and diagnosing, so it directly affects the diagnosing result. TheQRS wave group is not only the main but also the most prominent wave band of theECG. It serves as the pre-requisite of detecting the other waves. P wave and R waveare also important in diagnose. Through researching the shape of the clinical QRScompound wave, a new algorithm of using Marr wavelet chain in detecting QRS wavegroup is proposed according to the wavelet multi-resolution analysis and the modulusmaxima detection principle. The ECG is transformed in three kinds of scale to locatethe R wave, and ultimately select the R wave location in the way of voting the locatedpeak sampling points. When the R wave is located, search Q,S wave forward andbackward. As for the P and T wave, enlarge the scale and use the same method as theabove to search them. According to the inspection of authorized MIT-BIH arrhythmiadatabase, the accuracy rate of QRS wave group is as high as99.45%, that of the Pwave and T wave reached98.55%, which provides an accurate detection method for characteristic wave locating.