QRS Detection Using Zero Crossing Counts

Summary There is a novel technique for the detection of QRS complexes in electrocardiographic signals that is based on a feature obtained by counting the number of zero crossings per segment. It is well-known that zero crossing methods are robust against noise and are particularly useful for finite precision arithmetic. The new detection method inherits this robustness and provides a high degree of detection performance even in cases of very noisy electrocardiographic signals. Furthermore, due to the simplicity of detecting and counting zero crossings, the proposed technique provides a computationally efficient solution to the QRS detection problem. The excellent performance of the algorithm is confirmed by a sensitivity of 99.70% (277 false negatives) and a positive predictivity of 99.57% (390 false positives) against the MIT-BIH arrhythmia database.

[1]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[2]  W.J. Tompkins,et al.  Neural-network-based adaptive matched filtering for QRS detection , 1992, IEEE Transactions on Biomedical Engineering.

[3]  Beverly C. Yu,et al.  A Nonlinear Digital Filter For Cardiac QRS Complex Detection , 1985 .

[4]  Kang-Ping Lin,et al.  QRS feature extraction using linear prediction , 1989, IEEE Transactions on Biomedical Engineering.

[5]  W J Tompkins,et al.  Applications of artificial neural networks for ECG signal detection and classification. , 1993, Journal of electrocardiology.

[6]  Kenneth M. Kempner,et al.  A QRS Preprocessor Based on Digital Differentiation , 1971 .

[7]  S. Suppappola,et al.  Nonlinear transforms of ECG signals for digital QRS detection: a quantitative analysis , 1994, IEEE Transactions on Biomedical Engineering.

[8]  P.E. Trahanias,et al.  An approach to QRS complex detection using mathematical morphology , 1993, IEEE Transactions on Biomedical Engineering.

[9]  A. Ruha,et al.  A real-time microprocessor QRS detector system with a 1-ms timing accuracy for the measurement of ambulatory HRV , 1997, IEEE Transactions on Biomedical Engineering.

[10]  P. W. MacFarlane,et al.  Trends in computer processed electrocardiograms , 1978 .

[11]  H. T. Nagle,et al.  A comparison of the noise sensitivity of nine QRS detection algorithms , 1990, IEEE Transactions on Biomedical Engineering.

[12]  Masahiko Okada,et al.  A Digital Filter for the ORS Complex Detection , 1979, IEEE Transactions on Biomedical Engineering.

[13]  M. Okada.  A digital filter for the QRS complex detection. , 1979, IEEE transactions on bio-medical engineering.

[14]  A Ligtenberg,et al.  A robust-digital QRS-detection algorithm for arrhythmia monitoring. , 1983, Computers and biomedical research, an international journal.

[15]  Willis J. Tompkins,et al.  Quantitative Investigation of QRS Detection Rules Using the MIT/BIH Arrhythmia Database , 1986, IEEE Transactions on Biomedical Engineering.

[16]  Willis J. Tompkins,et al.  Biomedical Digital Signal Processing , 1993 .

[17]  Mats-Erik Nygards,et al.  Adaptive QRS Detection Based on Maximum A Posteriori Estimation , 1982, IEEE Transactions on Biomedical Engineering.

[18]  W.J. Tompkins,et al.  ECG beat detection using filter banks , 1999, IEEE Transactions on Biomedical Engineering.

[19]  Willis J. Tompkins,et al.  Automated High-Speed Analysis of Holter Tapes with Microcomputers , 1983, IEEE Transactions on Biomedical Engineering.

[20]  S Akselrod,et al.  Nonlinear high pass filter for R-wave detection in ECG signal. , 1997, Medical engineering & physics.

[21]  G. Boudreaux-Bartels,et al.  Wavelet transform-based QRS complex detector , 1999, IEEE Transactions on Biomedical Engineering.

[22]  C. Li,et al.  Detection of ECG characteristic points using wavelet transforms. , 1995, IEEE transactions on bio-medical engineering.

[23]  Ed. McKenzie.  10. Time Series Analysis by Higher Order Crossings , 1996 .

[24]  R. Poli,et al.  Genetic design of optimum linear and nonlinear QRS detectors , 1995, IEEE Transactions on Biomedical Engineering.

[25]  Ewaryst Tkacz,et al.  A new parallel concept for QRS complex detector , 1992, 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[26]  M E Nygårds,et al.  An automated system for ECG monitoring. , 1979, Computers and biomedical research, an international journal.