Development of robust, fast and efficient QRS complex detector: a methodological review
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Alwan A (2014) Global status report on noncommunicable diseases 2014. World Health Organization, Geneva
Benjamin EJ (2018) Heart disease and stroke statistics update: a report from the American Heart Association. AHA statistical update. Circulation 137:e67–e492
Goss J (2008) Projection of Australian health care expenditure by disease, 2003 to 2033. Australian Institute of Health and Welfare, Canberra
Dilaveris P, Gialafos E, Sideris S, Theopistou A, Andrikopoulos GK (1998) Simple electrocardiographic markers for the prediction of paroxysmal idiopathic atrial fibrillation. Am Heart J 135(5):733–738
Jenkins D (2009) A (not so) brief history of electrocardiography. http://www.ecglibrary.com/ecghist.html
Benali R, Reguig FB, Slimane ZH (2012) Automatic classification of heartbeats using wavelet neural network. J Med Syst 36(2):883–892
Tsipouras M, Fotiadis D, Sideris D (2002) Arrhythmia classification using the RR-interval duration signal. In: Computer in cardiology, pp 485–488
Thong T, McNames J, Aboy M, Goldstein B (2004) Prediction of paroxysmal atrial fibrillation by analysis of atrial premature complexes. IEEE Trans Biomed Eng 51(4):561–569
Bashour C, Visinescu M, Gopakumaran B, Wazni O, Carangio F (2004) Characterization of premature atrial contraction activity prior to the onset of postoperative atrial fibrillation in cardiac surgery patients. Chest 126(4):831S
de Chazal P, O’Dwyer M, Reilly R (2004) Automatic classification of heartbeats using ecg morphology and heartbeat interval features. IEEE Trans Biomed Eng 51(7):1196–1206
Krasteva V, Jekova I, Christov I (2004) Automatic detection of premature atrial contractions in the electrocardiogram. Electrotech Electron E E 3(2):132–137
Raj S, Chand GP, Ray KC (2015) Arm-based arrhythmia beat monitoring system. Microprocess Microsyst 39(7):504–511
Raj S, Ray KC (2017) ECG signal analysis using DCT-based DOST and PSO optimized SVM. IEEE Trans Instrum Meas 66(3):470–478
Raj S, Ray KC, Shankar O (2016) Cardiac arrhythmia beat classification using DOST and PSO tuned SVM. Comput Methods Programs Biomed 136:163–177
Raj S, Ray KC (2018) Sparse representation of ECG signals for automated recognition of cardiac arrhythmias. Expert Syst Appl 105:49–64
Zapanta L, Poon CS, White D, Marcus C, Katz E (2004) Heart rate chaos in obstructive sleep apnea in children. In: 26th Annual international conference of the IEEE Engineering in Medicine and Biology Society (IEMBS), vol 2, pp 3889–3892
Shouldice R, Brien LO, Brien CO, de Chazal P, Gozal D (2004) Detection of obstructive sleep apnea in pediatric subjects using surface lead electrocardiogram features. Sleep 27(4):784–792
Scholz U, Bianchi A, Cerutti S, Kubicki S (1997) Vegetative background of sleep: spectral analysis of the heart rate variability. Physiol Behav 62(5):1037–1043
Trinder J, Kleiman J, Carrington M, Smith S, Breen S (2001) Autonomic activity during human sleep as a function of time and sleep stage. J Sleep Res 10(4):253–264
Jeppsen J, Beniczky S, Fuglsang FA, Sidenius P, Johansen P (2017) Modified automatic R-peak detection algorithm for patients with epilepsy using a portable electrocardiogram recorder. In: 39th Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp 4082-4085
Song J, Yan H, Xu Z, Yu X, Zhu R (2011) Myocardial ischemia analysis based on electrocardiogram QRS complex. Australas Phys Eng Sci Med 34(4):515–521
Moody G, Mark R (2001) The impact of the MIT-BIH arrhythmia database. IEEE Eng Med Biol Mag 20(3):45–50
Sufi F, Fang Q, Cosic I (2007) ECG R-R peak detection on mobile phones. In: 29th Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBS), pp 3697–3700
Morizet-Mahoudeaux P, Moreau C, Moreau D, Quarante JJ (1981) Simple microprocessor based system for on-line ECG arrhythmia analysis. Med Biol Eng Comput 19(4):l497–500
Friesen G, Jannett T, Jadallah M, Yates S, Quint S, Nagle H (1990) A comparison of the noise sensitivity of nine QRS detection algorithms. IEEE Trans Biomed Eng 37(1):85–98
Menrad A (1981) Dual microprocessor system for cardiovascular data acquisition, processing and recording. In: Proceedings of the 1981 IEEE international conference on industrial electronics, control and instrumentation, pp 64–69
Holsinger WP, Kempner KM, Miller MH (1971) A QRS preprocessor based on digital differentiation. IEEE Trans Biomed Eng 18(3):212–217
Balda R, Diller G, Deardorff E, Doue J, Hsieh P (1977) The HP ECG analysis program. In: van Bemmel JH, Willems JL (eds) Trends in computer-processed electrocardiograms. North-Holland Publishing, Amsterdam, pp 197–205
Ahlstrom ML, Tompkins WJ (1983) Automated high-speed analysis of Holter tapes with microcomputers. IEEE Trans Biomed Eng 30(10):651–657
Engelse W, Zeelenberg C (1979) A single scan algorithm for QRS-detection and feature extraction. In: IEEE proceedings of computers in cardiology
Ligtenberg A, Kunt M (1983) A robust-digital QRS-detection algorithm for arrhythmia monitoring. Comput Biomed Res 16(3):273–286
Dokur Z, Olmez T, Yazgan E, Ersoy O (1997) Detection of ECG waveforms by neural networks. Med Eng Phys 19(8):738–741
Borjesson P, Pahlm O, Sornmo L, Nygards ME (1982) Adaptive QRS detection based on maximum a posteriori estimation. IEEE Trans Biomed Eng 29(5):341–351
Fancott T, Wong DH (1980) A minicomputer system for direct high speed analysis of cardiac arrhythmia in 24 h ambulatory ECG tape recordings. IEEE Trans Biomed Eng 27(12):685–693
Keselbrener L, Keselbrener M, Akselrod S (1997) Nonlinear high pass filter for R-wave detection in ECG signal. Med Eng Phys 19(5):481–484
Leski J, Tkacz E (1992) A new parallel concept for QRS complex detector. In: 14th Annual international conference of the IEEE Engineering in Medicine and Biology Society, vol 2, pp 555–556
Srnmo L, Pahlm O, Nygards M (1982) Adaptive QRS detection in ambulatory ECG monitoring: a study of performance. In: Proceedings of IEEE computers in cardiology
Christov I, Dotsinsky I, Daskalov I (1992) High-pass filtering of ECG signals using QRS elimination. Med Biol Eng Comput 30(2):253–256
Laguna P, Thakor N, Caminal P, Jane R (1990) Low-pass differentiators for biological signals with known spectra: application to ECG signal processing. IEEE Trans Biomed Eng 37(4):420–425
Thakor N, Webster J, Tompkins WJ (1984) Estimation of QRS complex power spectra for design of a QRS filter. IEEE Trans Biomed Eng 31(11):702–706
Thakor N, Zhu Y-S (1991) Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection. IEEE Trans Biomed Eng 38(8):785–794
Bayasi N, Saleh H, Mohammad B, Ismail M (2014) 65-nm ASIC implementation of QRS detector based on Pan and Tompkins algorithm. In: 10th International conference on innovations in information technology (INNOVATIONS), pp 84–87
Deepu C, Lian Y (2015) A joint QRS detection and data compression scheme for wearable sensors. IEEE Trans Biomed Eng 62(1):165–175
Chen H, Chen S (2003) A moving average based filtering system with its application to real-time QRS detection. In: Computers in cardiology, pp 585–588
Phukpattaranont P (2015) QRS detection algorithm based on the quadratic filter. Expert Syst Appl 42(11):4867–4877
Kumar S, Mohan N, Prabaharan P, Soman KP (2016) Total variation denoising based approach for R-peak detection in ECG signals. In: 6th International conference on advances in computing & communications (ICACC), Cochin, India, pp 697–705
Gliner V, Behar J, Yaniv Y (2018) Novel method to efficiently create an mHealth App: implementation of a real-time electrocardiogram R peak detector. JMIR mHealth uHealth 6(5):e118
Jain S, Ahirwal MK, Kumar A, Bajaj V, Singh GK (2017) QRS detection using adaptive filters: a comparative study. ISA Trans 66:362–375
Sharma T, Sharma KK (2017) QRS complex detection in ECG signals using locally adaptive weighted total variation denoising. Comput Biol Med 87:187–199
Suppappola S, Ying S (1994) Nonlinear transforms of ECG signals for digital QRS detection: a quantitative analysis. IEEE Trans Biomed Eng 41(4):397–400
Sun Y, Suppappola S, Wrublewski T (1992) Microcontroller-based real-time QRS detection. Biomed Instrum Technol 26(6):477–84
Doyle T, Dugan E, Humphries B, Newton R (2004) Discriminating between elderly and young using a fractal dimension analysis of centre of pressure. Int J Med Sci 1(1):11–20
Burrus C, Gopinath R, Guo H (1998) Introduction to wavelets and wavelet transforms. Prentice Hall, New Jersey
Strang G, Nguyen T (1996) Wavelets and filter banks. Wellesley-Cambridge Press, Wellesley
Elgendi M, Jonkman M, De Boer F (2009) R wave detection using Coiflets wavelets. In: 35th Annual Northeast IEEE bioengineering conference, pp 1–2
Ghaffari A, Mollakazemi M (2015) Robust fetal QRS detection from noninvasive abdominal electrocardiogram based on channel selection and simultaneous multichannel processing. Australas Phys Eng Sci Med 38(4):581–592
Dinh H, Kumar D, Pah N, Burton P (2001) Wavelets for QRS detection. Australas Phys Eng Sci Med 24(4):207–211
Song J, Yan H, Li Y, Mu K (2010) Research on electrocardiogram baseline wandering correction based on wavelet transform, QRS barycenter fitting, and regional method. Australas Phys Eng Sci Med 33(3):279–283
Yochum M, Renaud C, Jacquir S (2016) Automatic detection of P, QRS and T patterns in 12 leads ECG signal based on CWT. Biomed Signal Process Control 25:46–52
Qin Q, Li J, Yue Y, Liu C (2017) An adaptive and time-efficient ECG R-peak detection algorithm. J Healthc Eng. https://doi.org/10.1155/2017/5980541
Park J, Lee S, Park U (2017) R peak detection method using wavelet transform and modified Shannon energy envelope. J Healthc Eng. https://doi.org/10.1155/2017/4901017
Singh O, Sunkaria R (2017) ECG signal denoising via empirical wavelet transform. Australas Phys Eng Sci Med 40(1):219–229
Ahmed S, Al-Shrouf A, Abo-Zahhad M (2000) ECG data compression using optimal nonorthogonal wavelet transform. Med Eng Phys 22(1):39–46
Zheng X, Li Z, Shen L, Ji Z (2008) Detection of QRS complexes based on biorthogonal spline wavelet. In: International symposium on information science and engineering (ISISE), vol 2, pp 502–506
Szilagyi S, Szilagyi L (2000) Wavelet transform and neural-network-based adaptive filtering for QRS detection. In: Proceedings of the 22nd annual international conference of the IEEE Engineering in Medicine and Biology Society, vol 2, pp 1267–1270
Xiaomin X, Ying L (2005) Adaptive threshold for QRS complex detection based on wavelet transform. In: 27th Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBS), pp 7281–7284
Martinez J, Almeida R, Olmos S, Rocha A, Laguna P (2004) A wavelet-based ECG delineator: evaluation on standard databases. IEEE Trans Biomed Eng 51(4):570–581
Ruha A, Sallinen S, Nissila S (1997) A real-time microprocessor QRS detector system with a 1-ms timing accuracy for the measurement of ambulatory HRV. IEEE Trans Biomed Eng 44(3):159–167
Li Y, Yan H, Hong F (2012) A new approach of QRS complex detection based on matched filtering and triangle character analysis. Australas Phys Eng Sci Med 35(3):341–356
Eskofier B, Kornhuber J, Hornegger J (2008) Embedded QRS detection for noisy ECG sensor data using a matched filter and directed graph search. In: Proceedings of the 4th Russian-Bavarian conference on Biomedical Engineering, Zelenograd, Moscow, Russia
Afonso V, Tompkins WJ, Nguyen T, Luo S (1999) ECG beat detection using filter banks. IEEE Trans Biomed Eng 46(2):192–202
Mengda L, Vinod A, Samson S (2011) A new flexible filter bank for low complexity spectrum sensing in cognitive radios. J Signal Process Syst 62(2):205–215
Afonso V, Tompkins WJ, Nguyen T, Trautmann S, Luo S (1995) Filter bank-based processing of the stress ECG. In: 17th IEEE annual engineering conference in Medicine and Biology Society, vol 2, pp 887–888
Song-Kai Z, Jian-Tao W, Jun-Rong X (1988) The real-time detection of QRS-complex using the envelope of ECG. In: Proceedings of the annual international conference on IEEE Engineering in Medicine and Biology Society
Nygards M, Sornmo L (1983) Delineation of the QRS complex using the envelope of the ECG. Med Biol Eng Comput 21(5):538–547
Arzeno N, Deng Z-D, Poon C-S (2008) Analysis of first-derivative based QRS detection algorithms. IEEE Trans Biomed Eng 55(2):478–484
Benitez D, Gaydecki P, Zaidi A, Fitzpatrick A (2000) A new QRS detection algorithm based on the Hilbert transform. In: Computers in cardiology, pp 379–382
Arzeno N, Poon C-S, Deng Z-D (2006) Quantitative analysis of QRS detection algorithms based on the first derivative of the ECG. In: 28th Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBS), pp 1788–1791
Wang Z, Wong CM, Wan F (2017) Adaptive Fourier decomposition based R-peak detection for noisy ECG signals. In: 39th Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBS), pp 987–990
Huang N, Shen Z, Long S, Wu M, Shih H (1998) The empirical mode decomposition and Hilbert spectrum for nonlinear and nonstationary time series analysis. In: Proceedings of the Royal Society of London
Oukhellou L, Aknin P, Delechelle E (2006) Railway infrastructure system diagnosis using empirical mode decomposition and Hilbert transform. In: Proceedings of IEEE international conference on acoustics, speech and signal processing (ICASSP), vol 3
Damerval C, Meignen S, Perrier V (2005) A fast algorithm for bidimensional EMD. IEEE Signal Process Lett 12(10):701–704
Safari A, Hesar H, Mohebbi M, Faradji F (2016) A novel method for R-peak detection in noisy ECG signals using EEMD and ICA. In: 23rd Iranian conference on biomedical engineering, pp 155–158
Chu C-H, Delp E (1989) Impulsive noise suppression and background normalization of electrocardiogram signals using morphological operators. IEEE Trans Biomed Eng 36(2):262–273
Trahanias P (1993) An approach to QRS complex detection using mathematical morphology. IEEE Trans Biomed Eng 40(2):201–205
Zhang F, Lian Y (2007) Novel QRS detection by CWT for ECG sensor. In: IEEE biomedical circuits and systems conference (BIOCAS), pp 211–214
Gustafson D (1977) Automated VCG interpretation studies using signal analysis techniques, technical report R-1044. Charles Stark Draper Laboratory, Cambridge
Chen Y, Duan H (2005) A QRS complex detection algorithm based on mathematical morphology and envelope. In: 27th Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBS), pp 4654–4657
NingIvan X, Selesnick W (2013) ECG enhancement and QRS detection based on sparse derivatives. Biomed Signal Process Control 8(6):713–723
Manikandan MS, Ramkumar B (2014) Straightforward and robust QRS detection algorithm for wearable cardiac monitor. Healthc Technol Lett 1(1):40–44
Zhou Y, Hu X, Tang Z, Ahn AC (2016) Sparse representation-based ECG signal enhancement and QRS detection. Physiol Meas 37(12):2093–2110
Arteaga-Falconi J, Al Osman H, El Saddik A (2015) R-peak detection algorithm based on differentiation. In: IEEE 9th International symposium on intelligent signal processing (WISP), pp 1–4
Zhang F, Lian Y (2007) Electrocardiogram QRS detection using multiscale filtering based on mathematical morphology. In: 29th Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBS), pp 3196–3199
Ulusar U, Govindan R, Wilson J, Lowery C, Preissl H, Eswaran H (2009) Adaptive rule based fetal QRS complex detection using Hilbert transform. In: Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp 4666–4669
Lin C, Hu W, Chen C, Weng C (2008) Heart rate detection in highly noisy handgrip electrocardiogram. In: Computers in cardiology, pp 477–480
Zhang F, Wei Y, Lian Y (2009) Frequency-response masking based filter bank for QRS dection in wearable biomedical devices. In: IEEE international symposium on circuits and systems (ISCAS), pp 1473–1476
Vai M-I, Zhou L-G (2004) Beat-to-beat ECG ventricular late potentials variance detection by filter bank and wavelet transform as beat-sequence filter. IEEE Trans Biomed Eng 51(8):1407–1413
Kaplan D (1990) Simultaneous QRS detection and feature extraction using simple matched filter basis functions. In: Proceedings of computers in cardiology, pp 503–506
Hamilton P, Tompkins W (1988) Adaptive matched filtering for QRS detection. In: Proceedings of annual international conference of the IEEE Engineering in Medicine and Biology Society, pp 147–148
Xue Q, Hu Y, Tompkins WJ (1992) Neural-network-based adaptive matched filtering for QRS detection. IEEE Trans Biomed Eng 39(4):317–329
Lu Y, Xian Y, Chen J, Zheng Z (2008) A comparative study to extract the diaphragmatic electromyogram signal. In: International conference on BioMedical Engineering and Informatics (BMEI), vol 2, pp 315–319
Dinh H, Kumar D, Pah N, Burton P (2001) Wavelets for QRS detection. In: Proceedings of 23rd annual international conference of the IEEE Engineering in Medicine and Biology Society, vol 2, pp 1883–1887
Szilagyi L (1999) Wavelet-transform-based QRS complex detection in on-line Holter systems. In: 21st Annual conference and the 1999 annual fall meeting of the Biomedical Engineering Society Engineering in Medicine and Biology, BMES/EMBS, conference, proceedings of the first joint, vol 1
Shyu L-Y, Wu Y-H, Hu W (2004) Using wavelet transform and fuzzy neural network for VPC detection from the Holter ECG. IEEE Trans Biomed Eng 51(7):1269–1273
Alesanco A, Olmos S, Istepanian R, Garcia J (2003) A novel real-time multilead ECG compression and de-noising method based on the wavelet transform. In: Computers in cardiology, pp 593–596
Bothe H (1997) Neuro-fuzzy-methoden. Springer, Berlin
Zhang F, Lian Y (2009) Wavelet and Hilbert transforms based QRS complexes detection algorithm for wearable ECG devices in wireless body sensor networks. In: IEEE biomedical circuits and systems conference (BioCAS), pp 225–228
Zhou H-Y, Hou K-M (2008) Embedded real-time QRS detection algorithm for pervasive cardiac care system. In: 9th International conference on signal processing (ICSP), pp 2150–2153
Tang J, Yang X, Xu J, Tang Y, Zou Q, Zhang X (2008) The algorithm of R peak detection in ECG based on empirical mode decomposition. In: 4th International conference on natural computation (ICNC), vol 5, pp 624–627
Hongyan X, Minsong H (2008) A new QRS detection algorithm based on empirical mode decomposition. In: 2nd International conference on bioinformatics and biomedical engineering (ICBBE), pp 693–696
Arafat A, Hasan T (2009) Automatic detection of ECG wave boundaries using empirical mode decomposition. In: IEEE international conference on acoustics, speech, and signal processing (ICASSP), pp 461–464
Kew H-P, Jeong D-U (2011) Variable threshold method for ECG R-peak detection. J Med Syst 35(5):1085–1094
Zidelmal Z, Amirou A, Abdeslam DO, Moukadem A, Dieterlen A (2014) QRS detection using S-transform and Shannon energy. Comput Methods Programs Biomed 116(1):1–9
Dohare AK, Kumar V, Kumar R (2014) An efficient new method for the detection of QRS in electrocardiogram. Comput Electr Eng 40(5):1717–1730
Lin Z, Wang B, Chen H, Zhang Y, Wang X (2017) Design and implementation of a high quality R-peak detection algorithm. In: China semiconductor technology international conference (CSTIC), pp 1–3
Belforte G, De Mori R, Ferraris E (1979) A contribution to the automatic processing of electrocardiograms using syntactic methods. IEEE Trans Biomed Eng 26(3):125–136
Ciaccio E, Dunn S, Akay M (1993) Biosignal pattern recognition and interpretation systems. 2. Methods for feature extraction and selection. IEEE Eng Med Biol Mag 12(4):106–113
Trahanias P, Skordalakis E (1990) Syntactic pattern recognition of the ECG. IEEE Trans Pattern Anal Mach Intell 12(7):648–657
Vijaya G, Kumar V, Verma H (1998) ANN-based QRS-complex analysis of ECG. J Med Eng Technol 22(4):160–167
Hu YH, Tompkins WJ, Urrusti JL, Afonso VX (1993) Applications of artificial neural networks for ECG signal detection and classification. J Electrocardiol 26:66–73
Strintzis M, Stalidis G, Magnisalis X, Maglaveras N (1992) Use of neural networks for electrocardiogram (ECG) feature extraction recognition and classification. Neural Network World 3:313–328
Kohler B, Hennig C, Orglmeister R (2003) QRS detection using zero crossing counts. Appl Genomics Proteomics 2:138–145
Coast D, Stern R, Cano G, Briller S (1990) An approach to cardiac arrhythmia analysis using hidden Markov models. IEEE Trans Biomed Eng 37(9):826–836
Dobbs S, Schmitt N, Ozemek H (1984) QRS detection by template matching using real-time correlation on a microcomputer. J Clin Eng 9:197–212
Ebenezer D, Krishnamurthy V (1993) Wave digital matched filter for electrocardiogram preprocessing. J Biomed Eng 15(2):132–134
Di Virgilio V, Francaiancia C, Lino S, Cerutti S (1995) ECG fiducial points detection through wavelet transform. In: 17th Annual conference of the IEEE Engineering in Medicine and Biology Society, vol 2, pp 1051–1052
Rao K (1997) DWT based detection of R-peaks and data compression of ECG signals. IETE J Res 43(5):345–349
Kadambe S, Murray R, Boudreaux-Bartels G (1999) Wavelet transform-based QRS complex detector. IEEE Trans Biomed Eng 46(7):838–848
Abibullaev B, Seo H (2011) A new QRS detection method using wavelets and artificial neural networks. J Med Syst 35(4):683–691
Suzuki Y (1995) Self-organizing QRS-wave recognition in ECG using neural networks. IEEE Trans Neural Network 6(6):1469–1477
Garca-Berdons C, Narvez J, Fernndez U, Sandovalm F (1997) A new QRS detector based on neural network. IWANN: biological and artificial computation: from neuroscience to technology. Springer, Heidelberg, pp 1260–1269
Cost A, Cano G (1989) QRS detection based on hidden Markov modeling. In: Proceedings of annual international conference on IEEE Engineering in Medicine and Biology Society, images of the twenty-first century, pp 34–35
Ayat M, Shamsollahi M, Mozaffari B, Kharabian S (2009) ECG denoising using modulus maxima of wavelet transform. In: Annual international conference of IEEE Engineering in Medicine and Biology Society (EMBC), pp 416–419
Moraes J, Freitas M, Vilani F, Costa E (2002) A QRS complex detection algorithm using electrocardiogram leads. In: Computers in cardiology, pp 205–208
Manikandan MS, Soman KP (2012) A novel method for detecting R-peaks in electrocardiogram (ECG) signal. Biomed Signal Process Control 7(2):118–128
Mallat S, Hwang W (1992) Singularity detection and processing with wavelets. IEEE Trans Inf Theory 38(2):617–643
Ravanshad N, Rezaee-Dehsorkh H, Lotfi R, Lian Y (2014) A level-crossing based QRS-detection algorithm for wearable ECG sensors. IEEE J Biomed Health Inform 18(1):183–192
Varon C, Caicedo A, Testelmans D, Buyse B, Huffel S (2015) A novel algorithm for the automatic detection of sleep apnea from single-lead ECG. IEEE Trans Biomed Eng 62(9):2269–78
Zhang X, Lian Y (2014) A 300-mv 220-nw event-driven ADC with real-time QRS detection for wearable ECG sensors. IEEE Trans Biomed Circuits Syst 8(6):834–843
Alavi S, Saadatmand-Tarzjan M (2013) A new combinatorial algorithm for QRS detection. In: 3rd International conference on computer and knowledge engineering (ICCKE), pp 396–399
Bouaziz F, Boutana D, Benidir M (2014) Multiresolution wavelet-based QRS complex detection algorithm suited to several abnormal morphologies. IET Signal Process 8(7):774–782
Krimi S, Ouni K, Ellouze N (2008) An approach combining wavelet transform and hidden Markov models for ECG segmentation. In: 3rd International conference on information and communication technologies: from theory to applications (ICTTA), pp 1–6
Clifford G, Azuaje F, McSharry P (2006) Advanced methods and tools for ECG data analysis. Artech House, Inc, Norwood
Dokur Z, Imez T (2001) ECG beat classification by a novel hybrid neural network. Comput Methods Programs Biomed 66(2–3):167–81
Cheng W, Chan K (1998) Classification of electrocardiogram using hidden Markov models. In: Proceedings of the 20th annual international conference of the IEEE Engineering in Medicine and Biology Society, vol 1, pp 143–146
Coast D (1993) Segmentation of high-resolution ECGs using hidden Markov models. In: IEEE international conference on acoustics, speech, and signal processing (ICASSP), vol 1, pp 67–70
Poli R, Cagnoni S, Valli G (1995) Genetic design of optimum linear and nonlinear QRS detectors. IEEE Trans Biomed Eng 42(11):1137–1141
Chen H, Chan H (2006) A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising. Comput Methods Programs Biomed 82(3):187–195
Ghaffari A, Golbayani H, Ghasemi M (2008) A new mathematical based QRS detector using continuous wavelet transform. Comput Electr Eng 34(2):81–91
Zheng H, Wu J (2008) Real-time QRS detection method. In: 10th International conference on e-health networking, applications and services (HealthCom), pp 169–170
Fard P, Moradi M, Tajvidi M (2008) A novel approach in R peak detection using hybrid complex wavelet (HCW). Int J Cardiol 124(2):250–253
Christov II (2004) Real time electrocardiogram QRS detection using combined adaptive threshold. Biomed Eng Online 3(1):28
Elgendi M, Mahalingam S, Jonkman M, de Boer F (2008) A robust QRS complex detection algorithm using dynamic thresholds. In: International symposium on computer science and its applications (CSA), pp 153–158
Elgendi M, Jonkman M, De Boer F (2009) Improved QRS detection algorithm using dynamic thresholds. Int J hybrid Inf Technol 2:65–80
Li C, Zheng C, Tai C (1995) Detection of ECG characteristic points using wavelet transforms. IEEE Trans Biomed Eng 42(1):21–28
Afonso V, Tompkins WJ, Nguyen T, Luo S (1996) Filter bank-based ECG beat detection. In: Proceedings of the 18th annual international conference of the IEEE Engineering in Medicine and Biology Society, bridging disciplines for biomedicine, vol 3, pp 1037–1038
Chiarugi F, Sakkalis V, Emmanouilidou D, Krontiris T, Varanini M, Tollis I (2007) Adaptive threshold QRS detector with best channel selection based on a noise rating system. In: Computers in cardiology, pp 157–160
Chouhan V, Mehta S (2008) Detection of QRS complexes in 12-lead ECG using adaptive quantized threshold. Int J Comput Sci Network Secur 8:155–163
Chouakri S, Bereksi-Reguig F, Taleb-Ahmed A (2011) QRS complex detection based on multi wavelet packet decomposition. Appl Math Comput 217(23):9508–9525
Zidelmal Z, Amirou A, Adnane M, Belouchrani A (2012) QRS detection based on wavelet coefficients. Comput Methods Programs Biomed 107(3):490–496
Elgendi M (2013) Fast QRS detection with an optimized knowledge-based method: evaluation on 11 standard ECR databases. PLoS ONE 8(9):e73557
Elgendi M, Eskofier B, Dokos S, Abbott D (2014) Revisiting QRS detection methodologies for portable, wearable, battery-operated, and wireless ECG systems. PLoS ONE 9(1):1–18
Raj S, Luthra S, Ray KC (2015) Development of handheld cardiac event monitoring system. IFAC-PapersOnLine 48(4):71–76