An Efficient R-peak Detection Based on New Nonlinear Transformation and First-Order Gaussian Differentiator

Cardiovascular Engineering and Technology

Volumn 2, Issue 4, 2011, Pages 408-425

  Kathirvel, P ^b   Manikandan, M Sabarimalai ^a   Prasanna, S R M ^c   Soman, K P ^b  

^a AMRITA SCHOOL OF ENGINEERING   (India)

^b AMRITA UNIVERSITY   (India)

^c INDIAN INSTITUTE OF TECHNOLOGY GUWAHATI   (India)

Author keywords

ECG beat recognition; ECG signal analysis; Gaussian differentiator; Heart rate variability analysis; Peak finding logic; QRS complex detection; Shannon energy

Indexed keywords

ECG BEAT RECOGNITION; GAUSSIANS; HEART RATE VARIABILITY ANALYSIS; PEAK FINDING; QRS COMPLEX DETECTION; SHANNON ENERGY;

ALGORITHMS; COMPLEXATION; CONVOLUTION; ELECTROCARDIOGRAPHY; GAUSSIAN DISTRIBUTION; MATHEMATICAL TRANSFORMATIONS;

SIGNAL DETECTION;

ACCURACY; ALGORITHM; AMPLITUDE MODULATION; ARTICLE; AUTOANALYSIS; BANDPASS FILTERING; CONTROLLED STUDY; DIAGNOSTIC TEST ACCURACY STUDY; FALSE NEGATIVE RESULT; FALSE POSITIVE RESULT; FIRST ORDER GAUSSIAN DIFFERENTIATOR ALGORITHM; HEART ARRHYTHMIA; HEART RATE VARIABILITY; NOISE REDUCTION; NONLINEAR SYSTEM; NONLINEAR TRANSFORMATION; PEAK FINDING ALGORITHM; PREDICTIVE VALUE; PRIORITY JOURNAL; QRS COMPLEX; R WAVE; REFERENCE DATABASE; RELIABILITY; SENSITIVITY ANALYSIS; SHANNON ENERGY; SIGNAL DETECTION; SIGNAL PROCESSING; VALIDATION PROCESS;

EID: 82955193252     PISSN: 1869408X     EISSN: 18694098     Source Type: Journal    
DOI: 10.1007/s13239-011-0065-3     Document Type: Article

References (38)

1. Abdelliche, F., and A. Charef. R-peak detection using a complex fractional wavelet. In: International Conference on Electrical and Electronics Engineering, Bursa, 2009, pp. 267-270.
2. Abibullaev, B., and H. D. Seo. A new QRS detection method using wavelets and artificial neural networks. J. Med. Syst. 2010. doi: 10. 1007/s10916-009-9405-3.
3. Adnane, M., Z. Jiang, and S. Choi. Development of QRS detection algorithm designed for wearable cardiorespiratory system. Comput. Methods Programs Biomed. 93(1): 20-31, 2009.
4. Arzeno, N. M., Z.-D. Deng, and C.-S. Poon. Analysis of first-derivative based QRS detection algorithms. IEEE Trans. Biomed. Eng. 55(2): 478-484, 2008.
5. Benitez, S., P. A. Gaydecki, A. Zaidi, and A. P. Fitzpatrick. The use of the Hilbert transform in ECG signal analysis. Comput. Biol. Med. 31: 399-406, 2001.
6. Biel, L., O. Pettersson, L. Philipson, and P. Wide. ECG analysis: a new approach in human identification. IEEE Trans. Instrum. Meas. 50(3): 808-812, 2001.
7. Chen, Y. L., and H. L. Duan. A QRS complex detection algorithm based on mathematical morphology and envelope. In: Proceedings of 27th Annual International Conference of the IEEE EMBS, Shanghai, China, 2005, pp. 4654-4657.
8. Darrington, J. Towards real time QRS detection: a fast method using minimal pre-processing. Biomed. Signal Process. Control 1: 169-176, 2006.
9. Elgendi, M., M. Jonkman, and F. De Boer. R wave detection using Coiflets wavelets. In: IEEE 35th Annual Northeast Bioengineering Conference, Boston, MA, 2009, pp. 1-2.
10. El-Segaier, M., O. Lilja, S. Lukkarinen, L. Srnmo, R. Sepponen, and E. Pesonen. Computer-based detection and analysis of heart sound murmur. Ann. Biomed. Eng. 33(7): 937-942, 2005.
11. Gerencsr, L., G. Kozmann, and H. K. Zsuzsanna. The use of the SPSA method in ECG analysis. IEEE Trans. Biomed. Eng. 49(10): 1094-1101, 2002.
12. Ghaffari, A., H. Golbayani, and M. Ghasemi. A new mathematical based QRS detector using continuous wavelet transform. Comput. Electr. Eng. 34: 81-91, 2008.
13. Hadj Slimane, Z.-E., and A. Nait-Ali. QRS complex detection using empirical mode decomposition. Digit. Signal Process. Rev. J. 20(4): 1221-1228, 2010.
14. Hamilton, P. S., and W. J. Tompkins. Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database. IIEEE Trans. Biomed. Eng. 33: 1157-1165, 1986.
15. Hongyan, X., and H. Minsong. A new QRS detection algorithm based on empirical mode decomposition. In: Proceedings of the 2nd International Conference on Bioinformatics and Biomedical Engineering, 2008, pp. 693-696.
16. Huang, B., and Y. Wang, Detecting QRS complexes of two-channel ECG signals by using combined wavelet entropy. In: International Conference on Bioinformatics and Biomedical Engineering, Beijing, China, 2009, pp. 1-4.
17. Hughes, N. P. Probabilistic models for automated ECG interval analysis. PhD thesis, University of Oxford, 2006.
18. Kadambe, S., R. Murray, and G. F. B. Bartels. Wavelet transform-based QRS complex detector. IEEE Trans. Biomed. Eng. 46(7): 838-848, 1999.
19. Karvounis, E. C., M. G. Tsipouras, D. I. Fotiadis, and K. K. Naka. An automated methodology for fetal heart rate extraction from the abdominal electrocardiogram. IEEE Trans. Inf. Technol. Biomed. 11(6): 628-638, 2007.
20. Khler, B.-U., C. Hennig, and R. Orglmeister. The principles of software QRS detection. IEEE Eng. Med. Biol. Mag. 21: 42-57, 2002.
21. Kligfield, P., L. S. Gettes, and J. J. Bailey. Recommendations for the standardization and interpretation of the electrocardiogram: part I. The electrocardiogram and its technology: a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Cardiology Foundation; and the Heart Rhythm Society endorsed by the International Society for Computerized Electrocardiology. Heart Rhythm 4(3): 394-412, 2007.
22. Li, C., C. Zheng, and C. Tai. Detection of ECG characteristic points using wavelet transforms. IEEE Trans. Biomed. Eng. 42: 21-28, 1995.
23. Martnez, J. P., R. Almeida, S. Olmos, A. P. Rocha, and P. Laguna. A wavelet-based ECG delineator: evaluation on standard databases. IEEE Trans. Biomed. Eng. 51(4): 570-581, 2004.
24. Meyer, C., J. F. Gavela, and M. Harris. Combining algorithms in automatic detection of QRS complexes in ECG signals. IEEE Trans. Inf. Technol. Biomed. 10(3): 468-475, 2006.
25. Pahlm, O., and L. Srnmo. Software QRS detection in ambulatory monitoring-a review. Med. Biol. Eng. Comput. 22: 289-297, 1984.
26. Pan, J., and W. J. Tompkins. A real time QRS detection algorithm. IEEE Trans. Biomed. Eng. 32(3): 230-236, 1985.
27. Prasanna, S. R. M., and A. Subramanian. Finding pitch markers using first order Gaussian differentiator. In: IEEE Proceedings of the Third International Conference on Intelligent Sensing Information Process, 2005, pp. 140-145.
28. Romero, L., P. S. Addison, and N. Grubb. R-wave detection using continuous wavelet modulus maxima. IEEE Proc. Comput. Cardiol., 30: 565-568, 2003.
29. Sabarimalai Manikandan, M., and S. Dandapat. Wavelet threshold based TDL and TDR algorithms for real-time ECG signal compression. Biomed. Signal Process. Control 3: 44-66, 2008.
30. Sabarimalai Manikandan, M., and S. Dandapat. A novel method for detecting R-peaks in eletrocardiogram (ECG) signal. Biomed. Signal Process. Control, 2011. doi: 10. 1016/j. bspc. 2011. 03. 004.
31. Surez, K. V., J. C. Silva, Y. Berthoumieu, P. Gomis, and M. Najim. ECG beat detection using a geometrical matching approach. IEEE Trans. Biomed. Eng. 54(4): 485-489, 2007.
32. Tang, J., X. Yang, J. Xu, Y. Tang, Q. Zou, and X. Zhang. The algorithm of R Peak detection in ECG based on empirical mode decomposition. In: Fourth International Conference on Natural Computation, 2008, Vol. 5, pp. 624-627.
33. Thakor, N. V., J. G. Webster, and W. J. Tompkins. Estimation of QRS complex power spectra for design of a QRS filter. IEEE Trans. Biomed. Eng. 31: 702-706, 1984.
34. Trahanias, P. E. An approach to QRS complex detection using mathematical morphology. IEEE Trans. Biomed. Eng. 40(2): 201-205, 1993.
35. Y.-C. Yeha, and W.-J. Wanga. QRS complexes detection for ECG signal: the difference operation method. Comput. Methods Programs Biomed. 91: 245-254, 2008.
36. Zhang, F., and Y. Lian. QRS detection based on multi-scale mathematical morphology for wearable ECG devices in body area networks. IEEE Trans. Biomed. Circuits Syst. 3(4): 220-228, 2009.
37. Zhang, F., and Y. Lian. QRS detection based on morphological filter and energy envelope for applications in body sensor networks. J. Signal Process. Syst., 2009. doi: 10. 1007/s11265-009-0430-8.
38. Zhu, W., H. Zhao, and X. Chen. A new QRS detector based on empirical mode decomposition. In: IEEE 10th International Conference on Signal Processing (ICSP), 2010, pp. 1-4.