ECG Signal Preprocessing And R-wave Detection

Electrocardiograph (ECG) signal is synthetial refection of Cardiac Activity in body surface,and the ECG provides an important method to diagnoise cardiovascular diseases. Processing and analyzing ECG signal plays an important role in treating the cardiovascular diseases accurately.In this paper, ECG processing and recognition is introduced systematically. We mainly focus on the algorithm study of ECG preprocessing and R waveform detection, and obtain some good effects.The first has introduced the character of the ECG signal, the ECG waveform and the noises which corrupt the ECG signal. ECG is weak and it is extremely vulnerable to environmental impacts.Because of the mixed other biomedical signal and electromagnetic interference, the ECG signal is always with three major interference: frequency interference, muscle artifact and baseline drift.Then,with the different nature of ECG signal and noise, different methods were used to calibrate the noise.Adaptive coherent model was proposed to eliminate the power-line interference. The approach can get a noise template through detecting the section of the signal and computing the magnitude of interference, then subtract the noise template from the orginal signal,the processed signal without power-line interference can be got. The adaptive coherent model can adapt to change of frequency and amplitude of the interference. A morphological filtering approach was put forward to remove the noise of the ECG signals and to calibrate the base-line drift in this paper. Different sizes of structuring elements were used to process the signal for different duration of the characteristic wave and noise.Based on erosion and dilation,a class of generalized opening and closing morphological filter is constructed by using multiplr structuring elements.The results show that these filters can preserve the geometrical features well when they supress noise.For baseline correction,the signal is first filtered by a smaller size of structuring element for removing QRS complexes,Then the P,Twaveforms are removed by morphological filtering using a bigger size of structuring element.The final result is then an estimate of baseline drift.The correction of the baseline is then done by subtracting baseline drift from the original.As the QT intervals influenced by heart rate (HR) changing, the HR can be got through detecting R wave.Different sizes of structuring elements were used to process the signal for different HR. This method reduced the range of structuring elements, and keeps the ECG signal shape unchanged while calibrating the base-line drift effectively. Finally, a algorithm for detecting R-wave was proposed on the basis of mathematical morphological operation and wavelet transform.Mathematical morphology operation was used to extract QRS complexes, and the Mexihat wavelet transform was used to analyse the QRS complexes.Test results shows that the decetion method can detect accurately and localize precisely to R-wave of ECG signal.The ECG datebase in this paper is from MIT-BIH database, and all of algorithms are simulated on Matlab.