Research On ECG Signal Processing Method Of ECG Telemonitoring Diagnosis System

Cardiopathy is a chronic and severe disease that threats people's lives because of its high dangerousness. So it is important to research and develop the electrocardiogram (ECG) monitoring diagnosis system. Signal preprocessing and waveforms detection for ECG are the key of the ECG monitoring diagnosis system for diagnosis and therapy. At present, the available ECG signal processing methods have a lot of defects, so it is significant to research on the ECG signal processing methods.The methods of signal preprocessing, waveforms detection, classification and diagnosis for dynamic electrocardiogram (DCG) are studied in this dissertation. The ECG analytic algorithm and diagnostic software of the ECG telemonitoring diagnosis system by mobile telephone are also accomplished.At first, wavelet decomposing and reconstructing method and wavelet thresholding method are studied in this dissertation. The selection of wavelet basis is a main factor to influence the results of wavelet denoising method. Comparing the mathematical characteristic of eight kinds of wavelet basis, an optimal wavelet basis suited to the ECG signal is selected. Furthermore, the determination of the decomposing level is the other factor to affect the denoising results. So a new algorithm based on 3σ criterion is presented to determinate the wavelet decomposing level. It is more flexible and effective than the traditional method by trial and error to select the decomposing level.Although the wavelet thresholding method is widely used in the signal denoising, it has some underlying disadvantages. To overcome these disadvantages, an improved thresholding function is proposed firstly. Secondly, a new translation-invariant wavelet denoising method with the improved thresholding function is presented. It is effective in eliminating the myoelectric interference of ECG...