Research Of Distinguishing Principle For ECG Signal And Development Of Virtual ECG Analyzer

Electrocardiograph is an importance diagnostic tool to the heart disease. The processing and distinguishing method of ECG signal, the history and present situation of electrocardiograph at home and abroad are summarized and analyzed systematically in this paper. According to the great-acquired achievement in microelectronics, hardware and software of computer and modern signal processing in recent years, and combining these achievements with the virtual instrument technique, it is inevitable that the virtual instrument technique shall permeate into the field of biomedicine instrument, so a new instrument field, the virtual biomedical instrument, is formed.Noise reduction in ECG signal is the foundation and precondition of the ECG signal analysis and distinguishing. To counter the main noise of ECG signal, the interference and baseline drift, there are 11 kinds of the noise reduction to ECG signal analyzed and researched systematically in this paper. These methods can reduce the interference and baseline drift in the ECG signal effectively.An important function of automatic analysis system is the analysis and distinguishing to ECG signal accurately and reliably. The traditional distinguishing method of ECG signal is analyzed and researched systematically in this paper. These methods identify these waves of the ECG signal with the different mathematic characteristics of the different ECG waves. And these methods, such as the derivative of ECG signal, the template match, the shape characteristic match and so on, identify these characteristics of the ECG signal. Because the ECG signal is interfered by the various noise signals in the practical application, these methods cannot identify these characteristics of the ECG signal when the noise signal in ECG signal is serious. These methods have a definite practical value, whereas have their connatural localization.The wavelet transform has the time-frequency localization properties. The noise reduction principium and method of the noise interference in the ECG signal, the choice principle of the wavelet basis and its characteristic scales in which the various noise-signal of the ECG signal with the wavelet transform, are analyzed systematically in this paper. Combining the wavelet transform with the adaptive filter method, the adaptive filtering based on the wavelet transform is presented creatively in this paper to avoid the choice of threshold in the filter method based on the wavelet transform.Moreover, this method has the excellent filtering performance to the noise signal in the ECG signal. According to the singularity detection principium of the signal based on the wavelet transforms, the detection method of these R-waves in the ECG signal with the wavelet transforms is presented creatively in this paper. These methods in this paper can detect accurately and localize precisely to these R-waves in the ECG signal with the serious noise, and is applied to the detection of the heart rate real-timely and the identification of these R-waves in the ECG signal. Using the property of the band-pass filter of the wavelet transform, the distinguishing method of the P-waves, QRS complexes and T-waves of the ECG signal with the wavelet transform is presented creatively in this paper. This distinguishing method in this paper is excellent in the precision, and is an accurate analysis means for the automatic analysis of the ECG signal. It is the accurate quantitative analysis of the wavelet transform that the detection method of these R-waves and the distinguishing method of the P-waves, QRS complexes and T-waves in the ECG signal based on the wavelet transforms in this paper. Comparing these methods with the traditional qualitative analysis of the wavelet transform, there is the important practical value.Based on the research of the noise reduction, the analysis and distinguishing method in the ECG signal, and combining these research results in this paper with the virtual instrumentation technique, the biomedicine instrumentation, the virtual ECG analyzer ba...