The Denoising And Feature Extracting Based On Wavelets Transformation

Cardiac diseases are thought as a kind of major diseases which become more and more serious to human health.According to the Statistics of the WHO,it is about more than 1.2 million people died of Cardiac diseases,account for 25%of the total mortality. As the improving of the living standard,some unhealthy lifestyle would lead the diseases to the trend of rejuvenation.The characteristics of Cardiac diseases are:onset fast,high mortality rate,difficult to treat,expensive treatment cost.In order to overcome the danger of the diseases,early detection,diagnosis,and treatment will greatly decrease mortality rate.Family monitoring make it possible.In the family monitoring,to record the ECG conveniently and detect automatically are the most important.Electrocardiogram is a pictorial representation of the electrical activity of heart beats.Because of the direct relationship between the ECG waveform and interval of the heart beats,it is possible that doctor can diagnose cardiac disease and monitor patient conditions from the unususal ECG waveforms.QRS complex detection is the base of automatic analysis of ECG,which is mostly the first step of analysis and affects the following steps greatly.The difficulties of QRS detection lie in two factors:firstly,the physiological variability of QRS complex. Secondly,the various types of noises that can present in the ECG,for instance the power line noise,muscle noise,baseline drift.Using Multriesolution wavelet Analysis decomposed the ECG signal on multiscals, different frequency-bands of the signal were showed on different scales.Analysis signals in different frequency-bands.Based on the wavelet transform,this thesis introduces an algorithm to detect QRS complex.In particular,the quadratic spline wavelet has been adopted.The thesis first reviews wavelet transform briefly,and de-noise the ECG signal;then develops a QRS detention algorithm,which is then tested by using the MIH-BIH arrhythmia database. The result of experiments shows that the performance of models based on Quadratic Spline Wavelet is superior,and it can detect QRS complex exactly.We use this algorithm to identify and locate the R-Wave of the ECG.Based on the R-peak,find the R-start and R-end;and then locate the P-wave and T-wave;calculate the R-R intervals. The thesis emphasis on R-wave detection,R-R interval calculation,R-start and R-end determination.And then attempt to detect P-wave and T-wave.P and T detection is the nodus of ECG-detection.In the evaluation of the algorithm,contrast the detected data with original data,make statistical analysis,determine the accuracy of the algorithm.