The Dynamic ECG Analysis Based On Signal Quality Assessment

As the most serious threat in all disease, cardiovascular disease is a big damage to human health. As a comprehensive reflection on the surface of the heart activity, ECG has been widely used in the prevention and diagnosis of cardiovascular disease. Conventional ECG can record ECG of human being in a state repose, which mainly applies to clinical diagnosis or intensive care. Dynamic ECG can continuously record 24-hours ECG of daily activities, and effectively detect transient or paroxysmal arrhythmias and myocardial ischemia, making up for weakness of static ECG analysis that it can only deal with short-time and static data. Therefore, it is important to extract and analyze dynamic ECG of daily activities.Signal quality evaluation is to establish an evaluation standard of signal quality and noise intensity, and divide it into several different levels of quality. It is not directly to shape, denoise or extract feature to signal, but to get the signal quality index which reflects signal quality level to evaluate whole or partial data of signal based on the analysis of characteristics of the noise and waveform features. Compared with static ECG, dynamic ECG is subjected to greater and more complex noise interference, even will annihilate ECG, as the human being are active in the acquisition process. The low quality dynamic ECG signals not only increase the difficulty of signal processing, but also provide ineffective or incorrect information because of the unsatisfactory processing results, which influence the monitoring and diagnosis of disease. Therefore, it is necessary to do signal quality assessment of dynamic ECGThe thesis selects envelope, short-time energy and 1-5 Hz power spectrum density as quality evaluation parameters, defines the corresponding dynamic ECG signal quality assessment index. Based on the three signal quality assessment index, it puts forward the comprehensive quality evaluation algorithm of dynamic ECG. Then it achieves the signal quality assessment to dynamic ECG, and divides the ECG data into three levels of excellent, good, and poor, according to the evaluation results. In addition, it extracts R-wave of dynamic ECG signal after filtering by Mexican hat wavelet maxima, to test the quality assessment results of dynamic ECG, and analyzes heart rate according to R-wave information. The dynamic ECG analysis system based on signal quality assessment researches the signal quality assessment of dynamic ECG, R-wave detection and heart rate analysis.