Electrocardiogram QRS detection using multiscale filtering based on mathematical morphology.
A novel QRS detection algorithm based on multi-scale mathematical morphology (3M) and multi-frame differential modulus cumulation is proposed in this paper. The algorithm introduces the multi-stage filtering based on mathematical morphology from image processing field into ECG analysis to suppress the impulsive noise, and adopts multi-frame differential modulus cumulation to remove the baseline drift and enhance the signal. An average QRS detection rate of 99.67%, a sensitivity of 99.86% and a positive prediction of 99.80% have been achieved against the MIT/BIH Arrhythmia Database. Comparison with existing methods reveals that the proposed algorithm achieves better detection accuracy.
Zhang
Fei
F
Department of Electrical and Computer Engineering, National University of Singapore, 119260, Singapore. elezf@nus.edu.sg
Lian
Yong
Y
D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis* / Q000503:physiopathology*; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D006339:Heart Rate; D006801:Humans; D008433:Mathematics; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted