A New Multi-Window Detection Approach for P-Wave Boundary Points in Electrocardiograms Based on Bilateral Accumulative Area

Jian Wu, Riqing Chen, Yingsong Huang



Contributed papers (Oral)


01. Biomedical Signal Processing


08:30 - 10:00 | Wed 26 Aug | Space 2 | 1.4

Signal Processing in Physiological Systems IV: Cardiovascular Signals


This study presented an efficient and robust multi-window detection method for P-wave boundary points in electrocardiograms on the basis of bilateral accumulative area. Through mathematical analysis, the local extreme points of bilateral accumulative area curves were respectively found in a fitting parabola, which might be regarded as a significant indicator for the morphological characteristic of boundary points. And, the bilateral accumulative area curves of different window lengths had different sensitivities to the details and shapes of signals. With combination of the multi-window and 12-lead synchronous detection, the proposed method could screen the optimization boundary points from all extreme points of different window lengths, and adaptively match the P-wave location. The results of the proposed method were evaluated on the dataset-3 of the standard CSE database. As a result, the value of sensitivity Se = 97.8% was obtained for the detection of P-wave, with the standard deviations of 3.9 ms and 4.8 ms respectively for the onset and offset of P-wave.

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