Research on Biomedical Engineering
Research on Biomedical Engineering
Original article

Real-time premature ventricular contractions detection based on Redundant Discrete Wavelet Transform  

Ernano Arrais Junior, Ricardo Alexsandro de Medeiros Valentim, Gláucio Bezerra Brandão

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Introduction: Premature Ventricular Contraction (PVC) is among the most common types of ventricular cardiac arrhythmia. However, it only poses danger if the person suffers from a heart disease, such as heart failure. Hence, this is an important factor to consider in heart disease people. This paper presents an ECG real-time analysis system for PVC detection. Methods: This system is based on threshold adaptive methods and Redundant Discrete Wavelet Transform (RDWT), with a real-time approach. This analysis is based on wavelet coefficients energy for PVC detection. It is presented also a study to find the most indicated wavelet mother for ECG analysis application among the following wavelet families: Daubechies, Coiflets and Symlets. The system detection performance was validated on the MIT-BIH Arrhythmia Database. Results: The best results were verified with db2 wavelet
mother: the Sensitivity Se = 99.18%, Positive Predictive Value P+ = 99.15% and Specificity Sp = 99.94%, on 80.872 annotated beats, and 61.2 s processing speed for a half-hour record. Conclusion: The proposed system exhibits reliable PVC detection, with real-time approach, and a simple algorithmic structure that can be implemented in many platforms.


Electrocardiogram, Premature ventricular contraction, Redundant Discrete Wavelet Transform.


Andrade L, Leao MTP. Fault location for transmission lines using wavelet. IEEE Latin Am Trans. 2014; 12(6):1043-8.

Arrais E Jr, Valentim RAM, Brandão GB. Real time QRS detection based on redundant discrete wavelet transform. IEEE Latin Am Trans. 2016; 14(4):1662-8.

Arrais E, Roda VO, Sousa CM No, Ribeiro RLA, Costa FB. FPGA versus DSP for wavelet transform based voltage sags detection. In: Proceedings 2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC); 2014 May 12-15; Montevideo, Uruguay. USA: IEEE; 2014. p. 643-7.

Bortolan G, Degani R, Willems JL. ECG classification with neural networks and cluster analysis. Proc in Comp in Cardio. 1991; 1991:177-80.

Braunwald E, Antman EM, Beasley JW, Califf RM, Cheitlin MD, Hochman JS, Jones RH, Kereiakes D, Kupersmith J, Levin TN, Pepine CJ, Schaeffer JW, Smith EE 3rd, Steward DE, Theroux P, Gibbons RJ, Antman EM, Alpert JS, Faxon DP, Fuster V, Gregoratos G, Hiratzka LF, Jacobs AK, Smith SC Jr. ACC/AHA 2002 guideline update for the management of patients with unstable angina and non–st-segment elevation myocardial infarction: summary article. A report of the American College of Cardiology. J Am Coll Cardiol. 2002; 40(7):1366-74. PMid:12383588.

Burrus CS, Gopinath RA, Guo H. Introduction to wavelets and wavelet transforms: a primer. New Jersey: Prentice Hall; 1997.

Chazal P, O’Dwyer M, Reilly RB. Automatic classification of heartbeats using ecg morphology and heartbeat interval features. IEEE Trans Biomed Eng. 2004; 51(7):1196-206. PMid:15248536.

Chazal P, Reilly RB. A patient-adapting heartbeat classifier using ecg morphology and heartbeat interval features. IEEE Trans Biomed Eng. 2006; 53(12 Pt 1):2535-43. PMid:17153211.

Chong JW, Esa N, McManus DD, Chon KH. Arrhythmia discrimination using a smart phone. IEEE J Biol Health Info. 2015; 19(3):815-24. PMid:25838530.

Clifford GD, Azuaje F, McSharry PE, editors. Advanced methods and tools for ECG analysis. Vol. 1. Norwood: Artech House; 2006. (Series Engineering in Medicine and Biology).

Costa FB, Driesen J. Assessment of voltage sag indices based on scaling and wavelet coefficient energy analysis. IEEE Trans Power Deliv. 2013; 28(1):336-46.

Costa FB. Boundary wavelet coefficients for real-time detection of transients induced by faults and power-quality disturbances. IEEE Trans Power Deliv. 2014; 29(6):2674-87.

Dalvi RF, Zago GT, Andreao RV. Heartbeat classification system based on neural networks and dimensionality reduction. Res Biomed Eng. 2016; 32(4):318-26.

Daubechies I. Ten lectures on wavelets. Canada: Siam; 1992. (CBMS-NSF Regional Conference Series in Applied Mathematics).
Di Marco LY, Chiari L. A wavelet-based ECG delineation algorithm for 32-bit integer online processing. Biomed Eng Online. 2011; 10(1):1-19. PMid:21457580.

Dotsinsky IA, Stoyanov TV. Ventricular beat detection in single channel electrocardiograms. Biomed Eng Online. 2004; 3(1):1-9. PMid:14750981.

Gadêlha MFJ, Nicolosi DEC, França FFAC. Performance analysis of an interpretive electrocardiograph for use in a computer-aided diagnostic system for acute coronary syndromes. Rev Bras Eng Bioméd. 2012; 28(2):140-54.

Gagnon MP, Duplantie J, Fortin JP, Landry R. Implementing telehealth to support medical practice in rural/remote regions: what are the conditions for success? Imp Sci. 2006; 1(1):1-8. PMid:16930484.

Ge B, Ji KT, Ye HG, Li J, Li YC, Yin RP, Lin JF. Electrocardiogram features of premature ventricular contractions/ventricular tachycardia originating from the left ventricular outflow tract and the treatment outcome of radiofrequency catheter ablation. BMC Cardiovasc Disord. 2012; 12(1):1-11. PMid:23186541.

Goldberger ALL, Amaral AN, Glass L, Hausdorff JM, Ivanov PC, Mark RG, et al. Physiobank, physiotoolkit, and physionet: Components of a new research resource for complex physiologic signals. Comp Cardio. 2000; 101(23):215-20. PMID: 10851218.

Grossmann A, Morlet J. Decomposition of hardy functions into square integrable wavelets of constant shape. SIAM J Math Anal. 1984; 15(4):723-36.

Hamilton PS, Tompkins WT. Quantitative Investigation of QRS Detection Rules Using the MIT/BIH Arrhythmia Database. IEEE Trans Biomed Eng. 1986; 33(12):1157-65. PMid:3817849.

Hersh WR, Helfand M, Wallace J, Kraemer D, Patterson P, Shapiro S, Greenlick M. Clinical outcomes resulting from telemedicine interventions: A systematic review. BMC Med Inform

Decis Mak. 2001; 1(1):1-8. PMid:11737882.

Hirose H, Ishikawa S, Gotoh T, Kabutoya T, Kayaba K, Kajii E. Cardiac mortality of premature ventricular complexes in healthy people in Japan. J Cardiol. 2010; 56(1):23-6. PMid:20350513.

Hu YH, Palreddy S, Tompkins WJ. A patient-adaptable ecg beat classifier using a mixture of experts approach. IEEE Trans Biomed Eng. 1997; 44(9):891-900. PMid:9282481.

Inan OT, Giovangrandi L, Kovacs GTA. Robust neural-network-based classification of premature ventricular contractions using wavelet transform and timing interval features. IEEE Trans Biomed Eng. 2006; 53(12):2507-15.

Iwasa A, Hwa M, Hassankhani A, Liu T, Narayan SM. Abnormal heart rate turbulence predicts the initiation of ventricular arrhythmias. Pac Clin Electroph. 2005; 28(11):1189-97.

Jia L, Yue-Chun L, Kang-Ting J, Na-Dan Z, Jia-Xuan L, Wen-Wu Z, Peng-Lin Y, Ji-Fei T, Jia-Feng L. Premature ventricular contractions originating from the left ventricular septum: results of radiofrequency catheter ablation in twenty patients. BMC Cardio Disease. 2011; 11(1):1-8. PMid:21635765.

Kim J, Min SD, Lee M. An arrhythmia classification algorithm using a dedicated wavelet adapted to different subjects. Biomed Eng Online. 2011; 10(1):1-19. PMid:21707989.

Kohler BU, Hennig C, Orglmeister R. The principles of software QRS detection. IEEE Eng Med Biol Mag. 2002; 21(1):42-57. PMid:11935987.

Lek-uthai A, Ittatirut S, Teeramongkonrasmee A. Algorithm development for real-time detection of premature ventricular contraction. In: TENCON 2014 - 2014 IEEE Region 10 Conference; 2014 Oct 22-25; Bangkok, Thailand. USA: IEEE; 2014. p. 1-5.

Li C, Zheng C, Tai C. Detection of ECG characteristic points using wavelet transforms. IEEE Trans Biomed Eng. 1995; 42(1):21-8. PMid:7851927.

Lim JS. Finding features for real-time premature ventricular contraction detection using a fuzzy neural network system. IEEE Trans Neural Netw. 2009; 20(3):522-7. PMid:19179246.

Madeiro JPV, Cortez PC, Marques JAL. Performance comparison analysis of Wavelet and Hilbert transforms for QRS detection in ECG. Rev Bras Eng Bioméd. 2009; 25:153-66.

Mallat SG. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Mach Intell. 1989; 11(7):674-93.

Mallat SG. A wavelet tour of signal processing: the sparse way. USA: Academic Press; 2008.

Malmivuo J, Plonsey R. Bioelectromagnetism: principles and applications of bioelectric and biomagnetic fields. Oxford: Oxford University Press; 1995.

Mann DL, Zipes DP, Libby P, Bonow RO, editors. Braunwald’s heart disease: a textbook of cardiovascular medicine. Philadelphia: Saunders Elsevier; 2014.

Martinez J, Almeida R, Olmos S, Rocha A, Laguna P. A wavelet-based ecg delineator: evaluation on standard databases. IEEE Trans Biomed Eng. 2004; 51(4):570-81.

Martis RJ, Acharya UR, Adeli H. Current methods in electrocardiogram characterization. Comput Biol Med. 2014; 48:133-49. PMid:24681634.

Martis RJ, Acharya UR, Min LC. ECG beat classification using PCA, LDA, ICA and discrete wavelet transform. Biomed Signal Process Control. 2013; 8(5):437-48. 

Moody G, Mark R. The impact of the mit-bih arrhythmia database. IEEE Eng Med Biol Mag. 2001; 20(3):45-50. PMid:11446209.

Morris F, Brady WJ, Camm J. ABC of clinical electrocardiography. USA: John Wiley & Sons; 2009.

Natale A. Handbook of cardiac electrophysiology. Boca Raton: CRC Press; 2007.

Nazarahari M, Ghorbanpour Namin S, Davaie Markazi AH, Kabir Anaraki A. A multi-wavelet optimization approach using similarity measures for electrocardiogram signal classification. Biomed Sig Proc Cont. 2015; 20(400):142-51.

Nieminaki M, Ruha A, Kemppainen J, Nissila S, Myilyla R. Real-time detection of premature ventricular contraction using a matched filter bank. In: Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society; 1999 Oct 13-16; Atlanta, GA, USA. USA: IEEE; 1999. p. 269.

Orozco-Duque A, Martinez-Tabares FJ, Gallego J, Rodriguez CA, Mora ID, Castellanos-Dominguez G, et al. Classification of premature ventricular contraction based on discrete wavelet transform for real time applications. In: Health Care Exchanges (PAHCE) 2013 Pan American; 2013 Apr 29-May 4; Medellin, Colombia. USA: IEEE; 2013. p. 1-5.

Pan J, Tompkins WJ. A real-time QRS detection algorithm. IEEE Trans Biomed Eng. 1985; 32(3):230-6. PMid:3997178.

Pedireddi LB, Srinivasan B. Characterization of atmospheric turbulence effects and their mitigation using wavelet-based signal processing. IEEE Trans Commun. 2010; 58(6):1795-802.

Percival AT, Walden DB. Wavelet methods for time series analysis. New York: Cambridge University Press; 2000.

Saleh SA, Ahshan R, Moloney CR. Wavelet-based signal processing method for detecting ice accretion on wind turbines. IEEE Trans Sust Ener. 2012; 3(3):585-97.

Sasikala P, Wahidabanu R. Robust r peak and qrs detection in electrocardiogram using wavelet transform. Inter J of Advan Comp Sci and App-IJACSA. 2010; 1(6):48-53.

Sayadi O, Shamsollahi MB, Clifford GD. Robust detection of premature ventricular contractions using a wave-based Bayesian framework. IEEE Trans Biomed Eng. 2010; 57(2):353-62. PMid:19758851.

Shen Z, Hu C, Li P, Meng MQH. Research on premature ventricular contraction real-time detection based support vector machine. In: 2011 IEEE International Conference on Information and Automation (ICIA); 2011 June 6-8; Shenzhen, China. USA: IEEE; 2011. p. 864-9.

Shyu LY, Wu YH, Hu W. Using wavelet transform and fuzzy neural network for vpc detection from the holter ecg. IEEE Trans Biomed Eng. 2004; 51(7):1269-73. PMid:15248543.

Singh BN, Tiwari AK. Optimal selection of wavelet basis function applied to ECG signal denoising. Dig Sig Proc. 2006; 16(3):275-87.
Solosenko A, Petrenas A, Marozas V. Photoplethysmography-based method for automatic detection of premature ventricular contractions. IEEE Trans Biomed Circuits Syst. 2015; 9(5):662-9. PMid:26513800.

Thakor N, Webster J, Tompkins WJ. Estimation of QRS complex power spectra for design of a qrs filter. IEEE Trans Biomed Eng. 1984; 31(11):702-6. PMid:6500590.

Valentim RAM, Araújo BG, Guedes TAL. A telessaúde no Brasil e a inovação tecnológica na atenção primária. Natal: EDUFRN; 2015.
Wang J. Proposed new requirements for testing and reporting performance results of arrhythmia detection algorithms. In: Computing in Cardiology; 2013 Sept 22-25; Zaragoza, Spain. USA: IEEE; 2013. p. 967-70.

World Health Organization. WHO methods and data sources for country‐level causes of death 2000‐2015 [Internet]. Geneva: WHO; 2017 [cited 2018 Feb 28]. Available from:

Yochum M, Renaud C, Jacquir S. Automatic detection of p, qrs and t patterns in 12 leads ECG signal based on CWT. Biomed Sig Proc Contr. 2016; 25:46-52.

Zago GT, Andreão RV, Rodrigues SL, Mill JG, Sarcinelli M Fo. ECG-based detection of left ventricle hypertrophy. Res Biomed Eng. 2015; 31(2):125-32.

Zheng C, Li J, Lin JX, Wang LP, Lin JF. Where is the exact origin of narrow premature ventricular contractions manifesting qr in inferior wall leads? BMC Cardiol Diseas. 2016; 16(64):1-12. PMid:27044385.

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