[A new approach to wavelet-based P-wave detection].

According to the characteristics of four basic P morphologies, combining the wavelet transform and the amplitude and slope of transformed P wave, a new P-wave detecting method based on "wavelet-amplitude-slope" algorithm is presented: First search out all modulus maximum pairs to satisfy the threshold after wavelet transform, and then applying the amplitude and slope criterion exclude the interferes and detect the P peak and its shape, last determine the onset and end of P wave respectively which should be separately calculated for single-peak and double-peak P wave (or biphasic P wave). The approach is applied in experiments of data from MIT/BIH database and randomly collected data of clinical ECG. The experimental statistical results shows that the correct detecting rate is as high as 96% compared to manual annotation.

[Electrocardiographic signal feature extraction and its instrument development based on continuous wavelet transform].

This paper introduces a virtual recording and analysis instrumentation system for recording and identifying electrocardiographic (ECG) signals. The system developed is aimed at constructing a PC-based virtual instrumentation which enables to record. investigate and measure the ECG signal of 12 leads simultaneously and perfectly in order to improve the measuring precision of ECG. Based on the proper feature in time domain of Mexican hat wavelet expressed by positioning and analysis precision for QRS complex, the instrumentation system uses continuous wavelet transform(CWT) and uses the Mexican hat as the wavelet base to measure precisely the characteristic information and generate the precise characteristic parameters of ECG. The analysis of measured ECG signals in hospital demonstrated that even in the condition with serious noise interference, the method presented is still easily to describe the characteristics of ECG on line precisely which makes the instrumentation system valuable in practical application.