Study On Method Of Arrhythmia Diagnosis Based On Wavelet Analysis

Electrocardiogram (ECG) is a simple and practical approach for record of cardiac electrical activity. It can reflect the excitement in the heart of the dissemination process and the functional state of the heart. If the cardiac conduction system is obstacles or myocardial disease in a certain part, cardiac electrical activity can correct reflected the changes in a timely manner on the ECG, it showed as abnormal changes in the various waveform and of the evolutionary process. From 1903 ECG technology was used by Einthoven in clinical, it has been in the past 100 years, during the 100 years, the sustained development of ECG technology has made tremendous contributions to human life and health, biology, clinical medicine, it become indispensable, and most important in conventional techniques to clinical. In recent years, the cardiovascular and the cerebrovascular diseases morbidity and mortality increased year after year, to do regular checks of the heart, early detection of potential problems and has been accepted by most people, especially the needs of patients with heart disease. ECG examination as a conventional and necessary means of heart disease, is a doctor assistant diagnosis of heart disease, the accuracy of its interpretation is of great significance for the early detection of disease and improving national health standards and quality of life.In the current ECG data analysis, only a small number of automatically completed by the computer analysis. In the United States, there are about 8 million cases a year of automatic computer analysis, accounting for 10%; In Japan, there are about 1 million cases a year, accounting for 5%; China is of less application current. ECG diagnostic products, including GE Medical in the United States, Siemens Medical Corporation, and Mairui company, which is the leading domestic company. the ECG apparatus they provided, main function is ECG parameters data playback, waveform anomalies alarm, and display such as ST segment trend. In the hospital ECG is used more by inspections and monitoring, observation is only for doctors to see if the ECG is normal. The important reason for automatic analysis based on computer technology in the clinical analysis of the small proportion is the difficulties of waveform measurement and recognition, and the resulting caused by the wrong diagnosis. The paper is built on this backdrop.Papers were divided into six chapters, and the structure of the content is as follows:The first chapter describes a study of computer ECG diagnosis, that is, the significance of studying automatic diagnostic ECG and its presence in the clinical significance of medical and teaching aspects. Summed up the development of through the using of computer diagnostic ECG arrhythmia and the issues, and put forth the main content of this paper. This paper introduced the simulation analysis tools: MATLAB7.5 and data sources: MIT-BIH database.The second chapter describes the basic knowledge of the electrocardiogram. Including the formation of principle, and the characteristics of ECG, which reveals its support for the diagnostic value of arrhythmia.The third chapter gives a pretreatment to the ECG signal which will be used for analysis. First, research on characteristics of the three major noise (baseline drift, the frequency interference, electromyography interference) of ECG. Baseline drift which was significantly lower than the signal frequency band; The frequency band of frequency interference is higher than the band of waveform we want to extract; Electromyography interference's frequency band and the signal's are in aliasing.. To interface these features, introducing wavelet transform theory and we use it to decompose signal. Through low-frequency signal filtering to remove baseline drift; Through high-frequency signal filtering the details in addition to frequency interference; Finally, through the threshold value method eliminates the mechanical and electrical interference.Chapter IV, we respectively extract the waveform parameters and characteristics of the ECG. As the signal energy mainly concentrated in the third yardstick, Therefore, in the third scale wavelet decomposition, we find the R-determined position through finding extreme-right. In order to prevent misuse and missed the seizure, Design of the adaptive threshold has been done. After determining the location of R-wave, there is a appropriate fenestration before and after the R wave. We determine all other wave peak and the location of the start and finish though looking for maximum points, achieve the purpose of extracting characteristic parameters. And through MIT-BIH database validation, to good effect.Chapter V is for HRV analysis and the diagnosis of arrhythmia. Used of the RR interval during spectral analysis of HRV, extracted the IF / HF, variance, and other important parameters and discovered abnormal heart rate. Through the ECG arrhythmia analysis of seven common characteristics, we found these arrhythmias by the computer diagnosis. Finally first diagnosis method has been applied to the data in the records, compared to the experts'Notes, Achieved better consistency; then the actual patients were diagnosis, got the comparison of results by the doctors'diagnosis, Prove the practicality of the method.The chapter VI summarizes all this paper, briefs the job have done and the research results, and puts up some questions which should be researched continuously in the future.