P wave Detection in Electrocardiogram Based on Wavelet Transform and Differential Correction

The paper presents an improved algorithm of P wave peaks, onsets and offsets detection in Electrocardiogram (ECG). By reducing the impact of information loss during signal processing and detecting the effects of node errors, the algorithm can detect the P peaks, onsets and ends more quickly and accurately. For ECG signals, a denoising algorithm based on the Generalized Minmax Concave (GMC) penalty is used to remove power frequency interference, baseline drift and myoelectric interference. And then, the R wave peaks and the P wave peaks, onsets and ends are detected using the wavelet transform and the adaptive threshold, and the false detection rate is further reduced by the differential correction. The performance of the proposed algorithm is evaluated on QT database and sensitivity and positive predictivity of P wave detection reached 99.12% and 91.14%, respectively. Moreover, the proposed algorithm makes the detection of features such as P wave dispersion and P wave duration more accurate, which is beneficial to the diagnosis of diseases such as atrial fibrillation.