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Volumn 127, Issue , 2016, Pages 144-164

ECG-based heartbeat classification for arrhythmia detection: A survey

Author keywords

ECG based signal processing; Feature extraction; Heartbeat classification; Heartbeat segmentation; Learning algorithms; Preprocessing

Indexed keywords

DISEASES; ELECTROCARDIOGRAPHY; FEATURE EXTRACTION; HEART; LEARNING ALGORITHMS; SIGNAL DETECTION; SIGNAL PROCESSING; SURVEYS;

EID: 84953221679     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2015.12.008     Document Type: Article
Times cited : (723)

References (165)
  • 1
    • 34047224578 scopus 로고    scopus 로고
    • Advanced Methods And Tools for ECG Data Analysis
    • 1st ed. Artech House Publishers
    • [1] Clifford, G.D., Azuaje, F., McSharry, P., Advanced Methods And Tools for ECG Data Analysis. 1st ed., 2006, Artech House Publishers.
    • (2006)
    • Clifford, G.D.1    Azuaje, F.2    McSharry, P.3
  • 2
    • 34247189166 scopus 로고    scopus 로고
    • Multiadaptive bionic wavelet transform: application to ECG denoising and baseline wandering reduction
    • [2] Sayadi, O., Shamsollahi, M.B., Multiadaptive bionic wavelet transform: application to ECG denoising and baseline wandering reduction. EURASIP J. Adv. Signal Process. 2007:14 (2007), 1–11.
    • (2007) EURASIP J. Adv. Signal Process. , vol.2007 , Issue.14 , pp. 1-11
    • Sayadi, O.1    Shamsollahi, M.B.2
  • 3
    • 50049104061 scopus 로고    scopus 로고
    • ECG denoising and compression using a modified extended Kalman filter structure
    • [3] Sayadi, O., Shamsollahi, M.B., ECG denoising and compression using a modified extended Kalman filter structure. IEEE Trans. Biomed. Eng. 55:9 (2008), 2240–2248.
    • (2008) IEEE Trans. Biomed. Eng. , vol.55 , Issue.9 , pp. 2240-2248
    • Sayadi, O.1    Shamsollahi, M.B.2
  • 5
    • 0028960610 scopus 로고
    • Detection of ECG characteristic points using wavelet transforms
    • [5] Li, C., Zheng, C., Tai, C., Detection of ECG characteristic points using wavelet transforms. IEEE Trans. Biomed. Eng. 42:1 (1995), 21–28.
    • (1995) IEEE Trans. Biomed. Eng. , vol.42 , Issue.1 , pp. 21-28
    • Li, C.1    Zheng, C.2    Tai, C.3
  • 6
    • 0031023185 scopus 로고    scopus 로고
    • DSP implementation of wavelet transform for real time ECG wave forms detection and heart rate analysis
    • [6] Bahoura, M., Hassani, M., Hubin, M., DSP implementation of wavelet transform for real time ECG wave forms detection and heart rate analysis. Comput. Method Programs Biomed. 52:1 (2007), 35–44.
    • (2007) Comput. Method Programs Biomed. , vol.52 , Issue.1 , pp. 35-44
    • Bahoura, M.1    Hassani, M.2    Hubin, M.3
  • 7
    • 2942709662 scopus 로고    scopus 로고
    • Automatic classification of heartbeats using ECG morphology and heartbeat interval features
    • [7] de Chazal, P., O'Dwyer, M., Reilly, R.B., Automatic classification of heartbeats using ECG morphology and heartbeat interval features. IEEE Trans. Biomed. Eng. 51:7 (2004), 1196–1206.
    • (2004) IEEE Trans. Biomed. Eng. , vol.51 , Issue.7 , pp. 1196-1206
    • de Chazal, P.1    O'Dwyer, M.2    Reilly, R.B.3
  • 8
    • 84555190723 scopus 로고    scopus 로고
    • Weighted conditional random fields for supervised interpatient heartbeat classification
    • [8] de Lannoy, G., François, D., Delbeke, J., Verleysen, M., Weighted conditional random fields for supervised interpatient heartbeat classification. IEEE Trans. Biomed. Eng. 59:1 (2012), 241–247.
    • (2012) IEEE Trans. Biomed. Eng. , vol.59 , Issue.1 , pp. 241-247
    • de Lannoy, G.1    François, D.2    Delbeke, J.3    Verleysen, M.4
  • 9
    • 0033908714 scopus 로고    scopus 로고
    • Knowledge-based ECG interpretation: a critical review
    • [9] Kundu, M., Nasipuri, M., Basu, D.K., Knowledge-based ECG interpretation: a critical review. Pattern Recogn. 33:3 (2000), 351–373.
    • (2000) Pattern Recogn. , vol.33 , Issue.3 , pp. 351-373
    • Kundu, M.1    Nasipuri, M.2    Basu, D.K.3
  • 10
    • 0012485325 scopus 로고    scopus 로고
    • Testing and reporting performance results of cardiac rhythm and ST segment measurement algorithms
    • American National Standards Institute, Inc. (ANSI), Association for the Advancement of Medical Instrumentation (AAMI), ANSI/AAMI/ISO EC57, 1998-(R)2008
    • [10] ANSI/AAMI, Testing and reporting performance results of cardiac rhythm and ST segment measurement algorithms. 2008, American National Standards Institute, Inc. (ANSI), Association for the Advancement of Medical Instrumentation (AAMI), ANSI/AAMI/ISO EC57, 1998-(R)2008.
    • (2008)
    • ANSI/AAMI1
  • 11
    • 0020695647 scopus 로고
    • The nature of electrical propagation in cardiac muscle
    • [11] Spach, M.S., Kootsey, J.M., The nature of electrical propagation in cardiac muscle. Am. J. Physiol. Heart Circ. Physiol. 244:H (1983), 3–22.
    • (1983) Am. J. Physiol. Heart Circ. Physiol. , vol.244 , Issue.H , pp. 3-22
    • Spach, M.S.1    Kootsey, J.M.2
  • 12
    • 0018289307 scopus 로고
    • Waller-pioneer of electrocardiography
    • [12] Besterman, E., Creese, R., Waller-pioneer of electrocardiography. Br. Heart J. 42:1 (1979), 61–64.
    • (1979) Br. Heart J. , vol.42 , Issue.1 , pp. 61-64
    • Besterman, E.1    Creese, R.2
  • 14
    • 78650317618 scopus 로고    scopus 로고
    • Dry-contact and noncontact biopotential electrodes: methodological review
    • [14] Chi, Y.M., Jung, T.-P., Cauwenberghs, G., Dry-contact and noncontact biopotential electrodes: methodological review. IEEE Rev. Biomed. Eng. 3 (2010), 106–119.
    • (2010) IEEE Rev. Biomed. Eng. , vol.3 , pp. 106-119
    • Chi, Y.M.1    Jung, T.-P.2    Cauwenberghs, G.3
  • 16
    • 77956650689 scopus 로고    scopus 로고
    • The Six Second ECG: A Practical Guidebook to Basic ECG Interpretation
    • nursecom
    • [16] Barill, T., The Six Second ECG: A Practical Guidebook to Basic ECG Interpretation. 2003, nursecom.
    • (2003)
    • Barill, T.1
  • 17
    • 84864238440 scopus 로고    scopus 로고
    • An automatic patient-adapted ECG heartbeat classifier allowing expert assistance
    • [17] Llamedo, M., Martinez, J.P., An automatic patient-adapted ECG heartbeat classifier allowing expert assistance. IEEE Trans. Biomed. Eng. 59:8 (2012), 2312–2320.
    • (2012) IEEE Trans. Biomed. Eng. , vol.59 , Issue.8 , pp. 2312-2320
    • Llamedo, M.1    Martinez, J.P.2
  • 18
    • 84889610434 scopus 로고    scopus 로고
    • Electrocardiographic systems with reduced numbers of leads – synthesis of the 12-lead ECG
    • [18] Tomaŝić, I., Trobec, R., Electrocardiographic systems with reduced numbers of leads – synthesis of the 12-lead ECG. IEEE Rev. Biomed. Eng. 7 (2014), 126–142.
    • (2014) IEEE Rev. Biomed. Eng. , vol.7 , pp. 126-142
    • Tomaŝić, I.1    Trobec, R.2
  • 21
    • 27544448562 scopus 로고    scopus 로고
    • Methodological considerations in the design of trials for safety assessment of new drugs and chemical entities
    • [21] Pater, C., Methodological considerations in the design of trials for safety assessment of new drugs and chemical entities. Trials 6:1 (2005), 1–13.
    • (2005) Trials , vol.6 , Issue.1 , pp. 1-13
    • Pater, C.1
  • 22
    • 0014970585 scopus 로고
    • Recursive digital filters for biological signals
    • [22] Lynn, P., Recursive digital filters for biological signals. Med. Biol. Eng. Comput. 9:1 (1979), 37–43.
    • (1979) Med. Biol. Eng. Comput. , vol.9 , Issue.1 , pp. 37-43
    • Lynn, P.1
  • 23
    • 0020332050 scopus 로고
    • Fetal electrocardiogram enhancement by time-sequenced adaptive filtering
    • [23] Ferrara, E.R., Widraw, B., Fetal electrocardiogram enhancement by time-sequenced adaptive filtering. IEEE Trans. Biomed. Eng. 29:6 (1982), 458–460.
    • (1982) IEEE Trans. Biomed. Eng. , vol.29 , Issue.6 , pp. 458-460
    • Ferrara, E.R.1    Widraw, B.2
  • 24
    • 0020642320 scopus 로고
    • ECG enhancement by adaptive cancellation of electrosurgical interference
    • [24] Yelderman, M., Widrow, B., Cioffi, J.M., Hesler, E., Leddy, J.A., ECG enhancement by adaptive cancellation of electrosurgical interference. IEEE Trans. Biomed. Eng. 30:7 (1983), 392–398.
    • (1983) IEEE Trans. Biomed. Eng. , vol.30 , Issue.7 , pp. 392-398
    • Yelderman, M.1    Widrow, B.2    Cioffi, J.M.3    Hesler, E.4    Leddy, J.A.5
  • 25
    • 0026203883 scopus 로고
    • Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection
    • [25] Thakor, N.V., Zhu, Y.-S., Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection. IEEE Trans. Biomed. Eng. 38:8 (1991), 785–794.
    • (1991) IEEE Trans. Biomed. Eng. , vol.38 , Issue.8 , pp. 785-794
    • Thakor, N.V.1    Zhu, Y.-S.2
  • 26
    • 0026848861 scopus 로고
    • Neural-network-based adaptive matched filtering for QRS detection
    • [26] Xue, Q., Hu, Y.H., Tompkins, W.J., Neural-network-based adaptive matched filtering for QRS detection. IEEE Trans. Biomed. Eng. 39:4 (1992), 317–329.
    • (1992) IEEE Trans. Biomed. Eng. , vol.39 , Issue.4 , pp. 317-329
    • Xue, Q.1    Hu, Y.H.2    Tompkins, W.J.3
  • 27
    • 33646153511 scopus 로고    scopus 로고
    • Optimal selection of wavelet basis function applied to ECG signal denoising
    • [27] Singh, B.N., Tiwari, A.K., Optimal selection of wavelet basis function applied to ECG signal denoising. Digit. Signal Process. 16:3 (2006), 275–287.
    • (2006) Digit. Signal Process. , vol.16 , Issue.3 , pp. 275-287
    • Singh, B.N.1    Tiwari, A.K.2
  • 28
    • 33744914300 scopus 로고    scopus 로고
    • A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising
    • [28] Chen, S.-W., Chen, H.-C., Chan, H.-L., A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising. Comput. Method Programs Biomed. 82:3 (2006), 187–195.
    • (2006) Comput. Method Programs Biomed. , vol.82 , Issue.3 , pp. 187-195
    • Chen, S.-W.1    Chen, H.-C.2    Chan, H.-L.3
  • 29
    • 77954309290 scopus 로고    scopus 로고
    • Classification of the electrocardiogram signals using supervised classifiers and efficient features
    • [29] Zadeh, A.E., Khazaee, A., Ranaee, V., Classification of the electrocardiogram signals using supervised classifiers and efficient features. Comput. Method Programs Biomed. 99:2 (2010), 179–194.
    • (2010) Comput. Method Programs Biomed. , vol.99 , Issue.2 , pp. 179-194
    • Zadeh, A.E.1    Khazaee, A.2    Ranaee, V.3
  • 31
    • 77952696573 scopus 로고    scopus 로고
    • Analysis of multidomain features for ECG classification
    • [31] Soria, M.L., Martinez, J.P., Analysis of multidomain features for ECG classification. Comput. Cardiol., 2009, 561–564.
    • (2009) Comput. Cardiol. , pp. 561-564
    • Soria, M.L.1    Martinez, J.P.2
  • 33
    • 62249091791 scopus 로고    scopus 로고
    • Hierarchical support vector machine based heartbeat classification using higher order statistics and hermite basis function
    • [33] Park, K.S., Cho, B.H., Lee, D.H., Song, S.H., Lee, J.S., Chee, Y.J., Kim, I.Y., Kim, S.I., Hierarchical support vector machine based heartbeat classification using higher order statistics and hermite basis function. Comput. Cardiol., 2008, 229–232.
    • (2008) Comput. Cardiol. , pp. 229-232
    • Park, K.S.1    Cho, B.H.2    Lee, D.H.3    Song, S.H.4    Lee, J.S.5    Chee, Y.J.6    Kim, I.Y.7    Kim, S.I.8
  • 35
    • 84893972699 scopus 로고    scopus 로고
    • Heartbeat classification using disease-specific feature selection
    • [35] Zhang, Z., Dong, J., Luo, X., Choi, K.-S., Wu, X., Heartbeat classification using disease-specific feature selection. Comput. Biol. Med. 46 (2014), 79–89.
    • (2014) Comput. Biol. Med. , vol.46 , pp. 79-89
    • Zhang, Z.1    Dong, J.2    Luo, X.3    Choi, K.-S.4    Wu, X.5
  • 36
    • 84921028186 scopus 로고    scopus 로고
    • Heartbeat classification using decision level fusion
    • [36] Zhang, Z., Luo, X., Heartbeat classification using decision level fusion. Biomed. Eng. Lett. 4:4 (2014), 388–395.
    • (2014) Biomed. Eng. Lett. , vol.4 , Issue.4 , pp. 388-395
    • Zhang, Z.1    Luo, X.2
  • 37
    • 79952156441 scopus 로고    scopus 로고
    • Heartbeat classification using feature selection driven by database generalization criteria
    • [37] Llamedo, M., Martí nez, J.P., Heartbeat classification using feature selection driven by database generalization criteria. IEEE Trans. Biomed. Eng. 58:3 (2011), 616–625.
    • (2011) IEEE Trans. Biomed. Eng. , vol.58 , Issue.3 , pp. 616-625
    • Llamedo, M.1    Martí nez, J.P.2
  • 38
    • 84874580309 scopus 로고    scopus 로고
    • Combining general multi-class and specific two-class classifiers for improved customized ECG heartbeat classification
    • [38] Ye, C., Kumar, B.V.K., Coimbra, M.T., Combining general multi-class and specific two-class classifiers for improved customized ECG heartbeat classification. International Conference on Pattern Recognition (ICPR), 2012, 2428–2431.
    • (2012) International Conference on Pattern Recognition (ICPR) , pp. 2428-2431
    • Ye, C.1    Kumar, B.V.K.2    Coimbra, M.T.3
  • 41
    • 84901760066 scopus 로고    scopus 로고
    • Heartbeat classification using normalized RR intervals and morphological features
    • [41] Lin, C.-C., Yang, C.-M., Heartbeat classification using normalized RR intervals and morphological features. Math. Problem Eng. 2014 (2014), 1–11.
    • (2014) Math. Problem Eng. , vol.2014 , pp. 1-11
    • Lin, C.-C.1    Yang, C.-M.2
  • 42
    • 84903344707 scopus 로고    scopus 로고
    • A new hierarchical method for inter-patient heartbeat classification using random projections and RR intervals
    • [42] Huang, H., Liu, J., Zhu, Q., Wang, R., Hu, G., A new hierarchical method for inter-patient heartbeat classification using random projections and RR intervals. Biomed. Eng. Online 13 (2014), 1–26.
    • (2014) Biomed. Eng. Online , vol.13 , pp. 1-26
    • Huang, H.1    Liu, J.2    Zhu, Q.3    Wang, R.4    Hu, G.5
  • 43
  • 44
    • 6444240833 scopus 로고    scopus 로고
    • ECG beat classifier designed by combined neural network model
    • [44] Güler, I., Übeyli, E.D., ECG beat classifier designed by combined neural network model. Pattern Recogn. 38:2 (2005), 199–208.
    • (2005) Pattern Recogn. , vol.38 , Issue.2 , pp. 199-208
    • Güler, I.1    Übeyli, E.D.2
  • 45
    • 0020948396 scopus 로고
    • Development and evaluation of a 2-lead ECG analysis program
    • [45] Moody, G.B., Mark, R.G., Development and evaluation of a 2-lead ECG analysis program. Comput. Cardiol., 1982, 39–44.
    • (1982) Comput. Cardiol. , pp. 39-44
    • Moody, G.B.1    Mark, R.G.2
  • 48
    • 0022929617 scopus 로고
    • Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database
    • [48] Hamilton, P.S., Tompkins, W.J., Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database. IEEE Trans. Biomed. Eng. 33:12 (1986), 1157–1165.
    • (1986) IEEE Trans. Biomed. Eng. , vol.33 , Issue.12 , pp. 1157-1165
    • Hamilton, P.S.1    Tompkins, W.J.2
  • 49
    • 0021892137 scopus 로고
    • A real-time QRS detection algorithm
    • [49] Pan, J., Tompkins, W.J., A real-time QRS detection algorithm. IEEE Trans. Biomed. Eng. 32:3 (1985), 230–236.
    • (1985) IEEE Trans. Biomed. Eng. , vol.32 , Issue.3 , pp. 230-236
    • Pan, J.1    Tompkins, W.J.2
  • 50
    • 0029394907 scopus 로고
    • Genetic design of optimum linear and nonlinear QRS detectors
    • [50] Poli, R., Cagnoni, S., Valli, G., Genetic design of optimum linear and nonlinear QRS detectors. IEEE Trans. Biomed. Eng. 42:11 (1995), 1137–1141.
    • (1995) IEEE Trans. Biomed. Eng. , vol.42 , Issue.11 , pp. 1137-1141
    • Poli, R.1    Cagnoni, S.2    Valli, G.3
  • 52
    • 0036950331 scopus 로고    scopus 로고
    • Open source ECG analysis
    • [52] Hamilton, P., Open source ECG analysis. Comput. Cardiol., 2002, 101–104.
    • (2002) Comput. Cardiol. , pp. 101-104
    • Hamilton, P.1
  • 53
    • 0028205396 scopus 로고
    • Application of artificial neural networks for ECG signal detection and classification
    • [53] Hu, Y.H., Tompkins, W.J., Urrusti, J.L., Afonso, V.X., Application of artificial neural networks for ECG signal detection and classification. J. Eletrocardiol. 26:Suppl. (1990), 66–73.
    • (1990) J. Eletrocardiol. , vol.26 , pp. 66-73
    • Hu, Y.H.1    Tompkins, W.J.2    Urrusti, J.L.3    Afonso, V.X.4
  • 54
    • 46249107626 scopus 로고    scopus 로고
    • QRS complexes detection for ECG signal: the difference operation method
    • [54] Yeh, Y.-C., Wang, W.-J., QRS complexes detection for ECG signal: the difference operation method. Comput. Method Program Biomed. 91:3 (2008), 245–254.
    • (2008) Comput. Method Program Biomed. , vol.91 , Issue.3 , pp. 245-254
    • Yeh, Y.-C.1    Wang, W.-J.2
  • 55
    • 63649093019 scopus 로고    scopus 로고
    • A model-based Bayesian framework for ECG beat segmentation
    • [55] Sayadi, O., Shamsollahi, M.B., A model-based Bayesian framework for ECG beat segmentation. Physiol. Meas. 30:3 (2009), 335–352.
    • (2009) Physiol. Meas. , vol.30 , Issue.3 , pp. 335-352
    • Sayadi, O.1    Shamsollahi, M.B.2
  • 56
    • 84984877741 scopus 로고    scopus 로고
    • MIT-BIH ECG database
    • Available at:
    • [56] Massachusetts Institute of Technology, MIT-BIH ECG database. 2011 Available at: http://ecg.mit.edu/.
    • (2011)
    • Massachusetts Institute of Technology1
  • 57
    • 84984865821 scopus 로고    scopus 로고
    • AHA database
    • Available at:
    • [57] American Heart Association, AHA database. 1998 Available at: http://www.ahadata.com/.
    • (1998)
    • American Heart Association1
  • 58
    • 0025171427 scopus 로고
    • Standardisation and validation of medical decision support systems: the CSE project
    • [58] van Bemmel, J.H., Williams, J.L., Standardisation and validation of medical decision support systems: the CSE project. Method Inf. Med. 29:4 (1990), 261–262.
    • (1990) Method Inf. Med. , vol.29 , Issue.4 , pp. 261-262
    • van Bemmel, J.H.1    Williams, J.L.2
  • 62
    • 76849115999 scopus 로고    scopus 로고
    • ECG signal compression and classification algorithm with quad level vector for ECG holter system
    • [62] Kim, H., Yazicioglu, R.F., Merken, P., van Hoof, C., Yoo, H.-J., ECG signal compression and classification algorithm with quad level vector for ECG holter system. IEEE Trans. Inf. Technol. Biomed. 14:1 (2010), 93–100.
    • (2010) IEEE Trans. Inf. Technol. Biomed. , vol.14 , Issue.1 , pp. 93-100
    • Kim, H.1    Yazicioglu, R.F.2    Merken, P.3    van Hoof, C.4    Yoo, H.-J.5
  • 63
    • 0028211695 scopus 로고
    • Automatic detection of wave boundaries in multilead ECG signals: validation with the CSE database
    • [63] Laguna, P., Jané, R., Caminal, P., Automatic detection of wave boundaries in multilead ECG signals: validation with the CSE database. Comput. Biomed. Res. 27:1 (1994), 45–60.
    • (1994) Comput. Biomed. Res. , vol.27 , Issue.1 , pp. 45-60
    • Laguna, P.1    Jané, R.2    Caminal, P.3
  • 64
    • 0031367598 scopus 로고    scopus 로고
    • Selection of parameters from power spectral density, wavelet transforms and other methods for the automated interpretation of the ECG
    • [64] Celler, B., de Chazal, P., Selection of parameters from power spectral density, wavelet transforms and other methods for the automated interpretation of the ECG. IEEE International Conference on Digital Signal Processing (ICDSP), 1997, 71–74.
    • (1997) IEEE International Conference on Digital Signal Processing (ICDSP) , pp. 71-74
    • Celler, B.1    de Chazal, P.2
  • 66
    • 84866562436 scopus 로고    scopus 로고
    • Heartbeat classification using morphological and dynamic features of ECG signals
    • [66] Ye, C., Bhagavatula, V., Coimbra, M.T., Heartbeat classification using morphological and dynamic features of ECG signals. IEEE Trans. Biomed. Eng. 59:10 (2012), 2930–2941.
    • (2012) IEEE Trans. Biomed. Eng. , vol.59 , Issue.10 , pp. 2930-2941
    • Ye, C.1    Bhagavatula, V.2    Coimbra, M.T.3
  • 67
    • 33747277666 scopus 로고    scopus 로고
    • A platform for wide scale integration and visual representation of medical intelligence in cardiology: the decision support framework
    • [67] Exarchos, T.P., Tsipouras, M.G., Nanou, D., Bazios, C., Antoniou, Y., Fotiadis, D.I., A platform for wide scale integration and visual representation of medical intelligence in cardiology: the decision support framework. Comput. Cardiol., 2005, 167–170.
    • (2005) Comput. Cardiol. , pp. 167-170
    • Exarchos, T.P.1    Tsipouras, M.G.2    Nanou, D.3    Bazios, C.4    Antoniou, Y.5    Fotiadis, D.I.6
  • 68
    • 34447285485 scopus 로고    scopus 로고
    • A methodology for the automated creation of fuzzy expert systems for ischaemic and arrhythmic beat classification based on a set of rules obtained by a decision tree
    • [68] Exarchos, T.P., Tsipouras, M.G., Exarchos, C.P., Papaloukas, C., Fotiadis, D.I., Michalis, L.K., A methodology for the automated creation of fuzzy expert systems for ischaemic and arrhythmic beat classification based on a set of rules obtained by a decision tree. Artif. Intell. Med. 40:3 (2007), 187–200.
    • (2007) Artif. Intell. Med. , vol.40 , Issue.3 , pp. 187-200
    • Exarchos, T.P.1    Tsipouras, M.G.2    Exarchos, C.P.3    Papaloukas, C.4    Fotiadis, D.I.5    Michalis, L.K.6
  • 72
    • 77957849289 scopus 로고    scopus 로고
    • ECG beat classification using particle swarm optimization and radial basis function neural network
    • [72] Korürek, M., Doğan, B., ECG beat classification using particle swarm optimization and radial basis function neural network. Expert Syst. Appl. 37:12 (2010), 7563–7569.
    • (2010) Expert Syst. Appl. , vol.37 , Issue.12 , pp. 7563-7569
    • Korürek, M.1    Doğan, B.2
  • 73
    • 59649126172 scopus 로고    scopus 로고
    • Classification of ECG complexes using self-organizing CMAC
    • [73] Wen, C., Lin, T.-C., Chang, K.-C., Huang, C.-H., Classification of ECG complexes using self-organizing CMAC. Measurement 42:3 (2009), 399–407.
    • (2009) Measurement , vol.42 , Issue.3 , pp. 399-407
    • Wen, C.1    Lin, T.-C.2    Chang, K.-C.3    Huang, C.-H.4
  • 74
    • 77955313314 scopus 로고    scopus 로고
    • A new method for classification of ECG arrhythmias using neural network with adaptive activation function
    • [74] Özbay, Y., Tezel, G., A new method for classification of ECG arrhythmias using neural network with adaptive activation function. Digit. Signal Process. 20:4 (2010), 1040–1049.
    • (2010) Digit. Signal Process. , vol.20 , Issue.4 , pp. 1040-1049
    • Özbay, Y.1    Tezel, G.2
  • 76
    • 33846438201 scopus 로고    scopus 로고
    • Comparison of FCM, PCA and WT techniques for classification ECG arrhythmias using artificial neural network
    • [76] Ceylan, R., Özbay, Y., Comparison of FCM, PCA and WT techniques for classification ECG arrhythmias using artificial neural network. Expert Syst. Appl. 33:2 (2007), 286–295.
    • (2007) Expert Syst. Appl. , vol.33 , Issue.2 , pp. 286-295
    • Ceylan, R.1    Özbay, Y.2
  • 77
    • 74049158271 scopus 로고    scopus 로고
    • Robust algorithm for arrhythmia classification in ECG using extreme learning machine
    • [77] Kim, J., Shin, H.S., Shin, J., Lee, M., Robust algorithm for arrhythmia classification in ECG using extreme learning machine. BioMed. Eng. OnLine 8:1 (2009), 1–12.
    • (2009) BioMed. Eng. OnLine , vol.8 , Issue.1 , pp. 1-12
    • Kim, J.1    Shin, H.S.2    Shin, J.3    Lee, M.4
  • 79
    • 38649095183 scopus 로고    scopus 로고
    • Integration of independent component analysis and neural networks for ECG beat classification
    • [79] Yu, S.-N., Chou, K.-T., Integration of independent component analysis and neural networks for ECG beat classification. Expert Syst. Appl. 34:4 (2008), 2841–2846.
    • (2008) Expert Syst. Appl. , vol.34 , Issue.4 , pp. 2841-2846
    • Yu, S.-N.1    Chou, K.-T.2
  • 80
    • 56349170342 scopus 로고    scopus 로고
    • Selection of significant independent components for ECG beat classification
    • [80] Yu, S.-N., Chou, K.-T., Selection of significant independent components for ECG beat classification. Expert Syst. Appl. 36:2 (2009), 2088–2096.
    • (2009) Expert Syst. Appl. , vol.36 , Issue.2 , pp. 2088-2096
    • Yu, S.-N.1    Chou, K.-T.2
  • 81
    • 70349490443 scopus 로고    scopus 로고
    • A comparative analysis of principal component and independent component techniques for electrocardiograms
    • [81] Chawla, M., A comparative analysis of principal component and independent component techniques for electrocardiograms. Neural Comput. Appl. 18:6 (2009), 539–556.
    • (2009) Neural Comput. Appl. , vol.18 , Issue.6 , pp. 539-556
    • Chawla, M.1
  • 84
    • 32644482767 scopus 로고    scopus 로고
    • A fuzzy clustering neural network architecture for classification of ECG arrhythmias
    • [84] Özbay, Y., Ceylan, R., Karlik, B., A fuzzy clustering neural network architecture for classification of ECG arrhythmias. Comput. Biol. Med. 36:4 (2006), 376–388.
    • (2006) Comput. Biol. Med. , vol.36 , Issue.4 , pp. 376-388
    • Özbay, Y.1    Ceylan, R.2    Karlik, B.3
  • 85
    • 50049126632 scopus 로고    scopus 로고
    • Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal
    • [85] Asl, B.M., Setarehdan, S.K., Mohebbi, M., Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal. Artif. Intell. Med. 44:1 (2008), 51–64.
    • (2008) Artif. Intell. Med. , vol.44 , Issue.1 , pp. 51-64
    • Asl, B.M.1    Setarehdan, S.K.2    Mohebbi, M.3
  • 87
    • 0030131032 scopus 로고    scopus 로고
    • Classification of cardiac arrhythmias using fuzzy ARTMAP
    • [87] Ham, F.M., Han, S., Classification of cardiac arrhythmias using fuzzy ARTMAP. IEEE Trans. Biomed. Eng. 43:4 (1996), 425–429.
    • (1996) IEEE Trans. Biomed. Eng. , vol.43 , Issue.4 , pp. 425-429
    • Ham, F.M.1    Han, S.2
  • 88
    • 0034774017 scopus 로고    scopus 로고
    • ECG beat recognition using fuzzy hybrid neural network
    • [88] Osowski, S., Linh, T.H., ECG beat recognition using fuzzy hybrid neural network. IEEE Trans. Biomed. Eng. 48:11 (2001), 1265–1271.
    • (2001) IEEE Trans. Biomed. Eng. , vol.48 , Issue.11 , pp. 1265-1271
    • Osowski, S.1    Linh, T.H.2
  • 89
    • 1642265037 scopus 로고    scopus 로고
    • Support vector machine-based expert system for reliable heartbeat recognition
    • [89] Osowski, S., Hoai, L.T., Markiewicz, T., Support vector machine-based expert system for reliable heartbeat recognition. IEEE Trans. Biomed. Eng. 51:4 (2004), 582–589.
    • (2004) IEEE Trans. Biomed. Eng. , vol.51 , Issue.4 , pp. 582-589
    • Osowski, S.1    Hoai, L.T.2    Markiewicz, T.3
  • 90
    • 58349091028 scopus 로고    scopus 로고
    • A novel approach for classification of ECG arrhythmias: type-2 fuzzy clustering neural network
    • [90] Ceylan, R., Özbay, Y., Karlik, B., A novel approach for classification of ECG arrhythmias: type-2 fuzzy clustering neural network. Expert Syst. Appl. 36:3 (2009), 6721–6726.
    • (2009) Expert Syst. Appl. , vol.36 , Issue.3 , pp. 6721-6726
    • Ceylan, R.1    Özbay, Y.2    Karlik, B.3
  • 91
    • 43749102493 scopus 로고    scopus 로고
    • Recognition and classification system of arrhythmia using ensemble of neural networks
    • [91] Osowski, S., Markiewicz, T., Hoai, L.T., Recognition and classification system of arrhythmia using ensemble of neural networks. Measurement 41:6 (2008), 610–617.
    • (2008) Measurement , vol.41 , Issue.6 , pp. 610-617
    • Osowski, S.1    Markiewicz, T.2    Hoai, L.T.3
  • 92
    • 0036083108 scopus 로고    scopus 로고
    • Study of features based on nonlinear dynamical modeling in ECG arrhythmia detection and classification
    • [92] Owis, M.I., Abou-Zied, A.H., Youssef, A.B.M., Kadah, Y.M., Study of features based on nonlinear dynamical modeling in ECG arrhythmia detection and classification. IEEE Trans. Biomed. Eng. 49:7 (2002), 733–736.
    • (2002) IEEE Trans. Biomed. Eng. , vol.49 , Issue.7 , pp. 733-736
    • Owis, M.I.1    Abou-Zied, A.H.2    Youssef, A.B.M.3    Kadah, Y.M.4
  • 93
    • 59149084224 scopus 로고    scopus 로고
    • Adaptive neuro-fuzzy inference system for classification of ECG signals using Lyapunov exponents
    • [93] Übeyli, E.D., Adaptive neuro-fuzzy inference system for classification of ECG signals using Lyapunov exponents. Comput. Method Program Biomed. 93:3 (2009), 313–321.
    • (2009) Comput. Method Program Biomed. , vol.93 , Issue.3 , pp. 313-321
    • Übeyli, E.D.1
  • 94
    • 36348956823 scopus 로고    scopus 로고
    • Block-based neural networks for personalized ECG signal classification
    • [94] Jiang, W., Kong, G.S., Block-based neural networks for personalized ECG signal classification. IEEE Trans. Neural Netw. 18:6 (2007), 750–1761.
    • (2007) IEEE Trans. Neural Netw. , vol.18 , Issue.6 , pp. 750-1761
    • Jiang, W.1    Kong, G.S.2
  • 95
    • 77956649367 scopus 로고    scopus 로고
    • Local fractal dimension based ECG arrhythmia classification
    • [95] Mishra, A.K., Raghav, S., Local fractal dimension based ECG arrhythmia classification. Biomed. Signal Process. Control 5:2 (2010), 114–123.
    • (2010) Biomed. Signal Process. Control , vol.5 , Issue.2 , pp. 114-123
    • Mishra, A.K.1    Raghav, S.2
  • 96
    • 38649085923 scopus 로고    scopus 로고
    • Adaptive wavelet network for multiple cardiac arrhythmias recognition
    • [96] Lin, C., Du, Y., Chen, T., Adaptive wavelet network for multiple cardiac arrhythmias recognition. Expert Syst. Appl. 34:4 (2008), 2601–2611.
    • (2008) Expert Syst. Appl. , vol.34 , Issue.4 , pp. 2601-2611
    • Lin, C.1    Du, Y.2    Chen, T.3
  • 97
    • 84856230584 scopus 로고    scopus 로고
    • Feature extraction for ECG heartbeats using higher order statistics of WPD coefficients
    • [97] Kutlu, Y., Kuntalp, D., Feature extraction for ECG heartbeats using higher order statistics of WPD coefficients. Comput. Method Program Biomed. 105:3 (2012), 257–267.
    • (2012) Comput. Method Program Biomed. , vol.105 , Issue.3 , pp. 257-267
    • Kutlu, Y.1    Kuntalp, D.2
  • 98
    • 0034909765 scopus 로고    scopus 로고
    • ECG beat classification by a novel hybrid neural network
    • [98] Dokur, Z., Ölmez, T., ECG beat classification by a novel hybrid neural network. Comput. Method Program Biomed. 66:2-3 (2001), 167–181.
    • (2001) Comput. Method Program Biomed. , vol.66 , Issue.2-3 , pp. 167-181
    • Dokur, Z.1    Ölmez, T.2
  • 99
    • 23744458827 scopus 로고    scopus 로고
    • Wavelet transforms and the ECG: a review
    • [99] Addison, P.S., Wavelet transforms and the ECG: a review. Physiol. Meas. 26:5 (2005), 155–199.
    • (2005) Physiol. Meas. , vol.26 , Issue.5 , pp. 155-199
    • Addison, P.S.1
  • 101
    • 34248190653 scopus 로고    scopus 로고
    • Electrocardiogram beat classification based on wavelet transformation and probabilistic neural network
    • [101] Yu, S.-N., Chen, Y.-H., Electrocardiogram beat classification based on wavelet transformation and probabilistic neural network. Pattern Recogn. Lett. 28:10 (2007), 1142–1150.
    • (2007) Pattern Recogn. Lett. , vol.28 , Issue.10 , pp. 1142-1150
    • Yu, S.-N.1    Chen, Y.-H.2
  • 102
    • 28844500635 scopus 로고    scopus 로고
    • Support vector machine based arrhythmia classification using reduced features
    • [102] Song, M.H., Lee, J., Cho, S.P., Lee, K.J., Yoo, S.K., Support vector machine based arrhythmia classification using reduced features. Int. J. Control Autom. Syst. 3:4 (2005), 509–654.
    • (2005) Int. J. Control Autom. Syst. , vol.3 , Issue.4 , pp. 509-654
    • Song, M.H.1    Lee, J.2    Cho, S.P.3    Lee, K.J.4    Yoo, S.K.5
  • 103
    • 84878473520 scopus 로고    scopus 로고
    • ECG arrhythmia classification using a probabilistic neural network with a feature reduction method
    • [103] Wang, J.-S., Chiang, W.-C., Hsu, Y.-L., Yang, Y.-T.C., ECG arrhythmia classification using a probabilistic neural network with a feature reduction method. Neurocomputing 116:20 (2013), 38–45.
    • (2013) Neurocomputing , vol.116 , Issue.20 , pp. 38-45
    • Wang, J.-S.1    Chiang, W.-C.2    Hsu, Y.-L.3    Yang, Y.-T.C.4
  • 104
    • 33947248058 scopus 로고    scopus 로고
    • Detection of ECG arrhythmia using a differential expert system approach based on principal component analysis and least square support vector machine
    • [104] Polat, K., Güneş, S., Detection of ECG arrhythmia using a differential expert system approach based on principal component analysis and least square support vector machine. Appl. Math. Comput. 186:1 (2007), 898–906.
    • (2007) Appl. Math. Comput. , vol.186 , Issue.1 , pp. 898-906
    • Polat, K.1    Güneş, S.2
  • 106
    • 7044263116 scopus 로고    scopus 로고
    • Ranking of pattern recognition parameters for premature ventricular contractions classification by neural networks
    • [106] Christov, I., Bortolan, G., Ranking of pattern recognition parameters for premature ventricular contractions classification by neural networks. Phisyol. Meas. 25:5 (2004), 1281–1290.
    • (2004) Phisyol. Meas. , vol.25 , Issue.5 , pp. 1281-1290
    • Christov, I.1    Bortolan, G.2
  • 107
    • 14844283547 scopus 로고    scopus 로고
    • Physiobank, physiotoolkit, and physionet: Components of a new research resource for complex physiologic signals
    • database and tools available at:
    • [107] Goldberger, A.L., Amaral, L.A.N., Glass, L., Hausdorff, J.M., Ivanov, P.C., Mark, R.G., Mietus, J.E., Moody, G.B., Peng, C.-K., Stanley, H.E., Physiobank, physiotoolkit, and physionet: Components of a new research resource for complex physiologic signals. Circulation 101:23 (2000), 215–220 database and tools available at: http://www.physionet.org/.
    • (2000) Circulation , vol.101 , Issue.23 , pp. 215-220
    • Goldberger, A.L.1    Amaral, L.A.N.2    Glass, L.3    Hausdorff, J.M.4    Ivanov, P.C.5    Mark, R.G.6    Mietus, J.E.7    Moody, G.B.8    Peng, C.-K.9    Stanley, H.E.10
  • 108
    • 0028547556 scopus 로고
    • Floating search methods in feature selection
    • [108] Pudil, P., Novovicova, J., Kittler, J., Floating search methods in feature selection. Pattern Recogn. Lett. 15:11 (1994), 1119–1125.
    • (1994) Pattern Recogn. Lett. , vol.15 , Issue.11 , pp. 1119-1125
    • Pudil, P.1    Novovicova, J.2    Kittler, J.3
  • 110
    • 0032028297 scopus 로고    scopus 로고
    • Feature subset selection using a genetic algorithm
    • [110] Yang, J., Honavar, V., Feature subset selection using a genetic algorithm. IEEE Intell. Syst. Appl. 13:2 (1998), 44–49.
    • (1998) IEEE Intell. Syst. Appl. , vol.13 , Issue.2 , pp. 44-49
    • Yang, J.1    Honavar, V.2
  • 111
    • 33845523839 scopus 로고    scopus 로고
    • Feature selection based on rough sets and particle swarm optimization
    • [111] Wang, X., Yang, J., Teng, X., Xia, W., Jensen, R., Feature selection based on rough sets and particle swarm optimization. Pattern Recogn. Lett. 28:4 (2007), 459–471.
    • (2007) Pattern Recogn. Lett. , vol.28 , Issue.4 , pp. 459-471
    • Wang, X.1    Yang, J.2    Teng, X.3    Xia, W.4    Jensen, R.5
  • 112
    • 48749109333 scopus 로고    scopus 로고
    • Particle swarm optimization for parameter determination and feature selection of support vector machines
    • [112] Lin, S.-W., Ying, K.-C., Chen, S.-C., Lee, Z.-J., Particle swarm optimization for parameter determination and feature selection of support vector machines. Expert Syst. Appl. 35:4 (2008), 1817–1824.
    • (2008) Expert Syst. Appl. , vol.35 , Issue.4 , pp. 1817-1824
    • Lin, S.-W.1    Ying, K.-C.2    Chen, S.-C.3    Lee, Z.-J.4
  • 113
    • 0003922190 scopus 로고    scopus 로고
    • Pattern Classification
    • 2nd ed. Wiley-Interscience
    • [113] Duda, R.O., Hart, P.E., Stork, D.G., Pattern Classification. 2nd ed., 2000, Wiley-Interscience.
    • (2000)
    • Duda, R.O.1    Hart, P.E.2    Stork, D.G.3
  • 114
    • 33846516584 scopus 로고    scopus 로고
    • Pattern Recognition and Machine Learning
    • 1st ed. Springer
    • [114] Bishop, C.M., Pattern Recognition and Machine Learning. 1st ed., 2006, Springer.
    • (2006)
    • Bishop, C.M.1
  • 115
    • 85013709368 scopus 로고    scopus 로고
    • Pattern Recognition
    • 4th ed. Elsevier
    • [115] Theodoridis, S., Koutroumbas, K., Pattern Recognition. 4th ed., 2009, Elsevier.
    • (2009)
    • Theodoridis, S.1    Koutroumbas, K.2
  • 116
    • 58549090877 scopus 로고    scopus 로고
    • Combining recurrent neural networks with eigenvector methods for classification of ECG beats
    • [116] Übeyli, E.D., Combining recurrent neural networks with eigenvector methods for classification of ECG beats. Digit. Signal Process. 19:2 (2009), 320–329.
    • (2009) Digit. Signal Process. , vol.19 , Issue.2 , pp. 320-329
    • Übeyli, E.D.1
  • 119
    • 71349087690 scopus 로고    scopus 로고
    • A qualitative comparison of artificial neural networks and support vector machines in ECG arrhythmias classification
    • [119] Moavenian, M., Khorrami, H., A qualitative comparison of artificial neural networks and support vector machines in ECG arrhythmias classification. Expert Syst. Appl. 37:4 (2010), 3088–3093.
    • (2010) Expert Syst. Appl. , vol.37 , Issue.4 , pp. 3088-3093
    • Moavenian, M.1    Khorrami, H.2
  • 120
    • 0346586663 scopus 로고    scopus 로고
    • Smote: synthetic minority over-sampling technique
    • [120] Chawla, N.V., Bowyer, K.W., Kegelmeyer, W.P., Smote: synthetic minority over-sampling technique. J. Artif. Intell. Res. 16:1 (2002), 321–357.
    • (2002) J. Artif. Intell. Res. , vol.16 , Issue.1 , pp. 321-357
    • Chawla, N.V.1    Bowyer, K.W.2    Kegelmeyer, W.P.3
  • 121
    • 33646133912 scopus 로고    scopus 로고
    • Intelligent classification of electrocardiogram (ECG) signal using extended kalman filter (EKF) based neuro fuzzy system
    • [121] Meau, Y.P., Ibrahim, F., Narainasamy, S.A.L., Omar, R., Intelligent classification of electrocardiogram (ECG) signal using extended kalman filter (EKF) based neuro fuzzy system. Comput. Method Program Biomed. 82:2 (2006), 157–168.
    • (2006) Comput. Method Program Biomed. , vol.82 , Issue.2 , pp. 157-168
    • Meau, Y.P.1    Ibrahim, F.2    Narainasamy, S.A.L.3    Omar, R.4
  • 122
    • 5644259871 scopus 로고    scopus 로고
    • ECG beat classification using neuro-fuzzy network
    • [122] Mehmet, E., ECG beat classification using neuro-fuzzy network. Pattern Recogn. Lett. 25:15 (2004), 1715–1722.
    • (2004) Pattern Recogn. Lett. , vol.25 , Issue.15 , pp. 1715-1722
    • Mehmet, E.1
  • 123
    • 78651295386 scopus 로고    scopus 로고
    • Minimum complexity echo state network
    • [123] Rodan, A., Tiňo, P., Minimum complexity echo state network. IEEE Trans. Neural Netw. 22:1 (2011), 131–144.
    • (2011) IEEE Trans. Neural Netw. , vol.22 , Issue.1 , pp. 131-144
    • Rodan, A.1    Tiňo, P.2
  • 124
    • 68649088777 scopus 로고    scopus 로고
    • Reservoir computing approaches to recurrent neural network training
    • [124] Lukoševičius, M., Jaeger, H., Reservoir computing approaches to recurrent neural network training. Comput. Sci. Rev. 3:3 (2009), 127–149.
    • (2009) Comput. Sci. Rev. , vol.3 , Issue.3 , pp. 127-149
    • Lukoševičius, M.1    Jaeger, H.2
  • 125
    • 84860729558 scopus 로고    scopus 로고
    • ECG arrhythmia classification based on logistic model tree
    • [125] Mahesh, V., Kandaswamy, A., Vimal, C., Sathish, B., ECG arrhythmia classification based on logistic model tree. J. Biomed. Sci. Eng. 2:6 (2009), 405–411.
    • (2009) J. Biomed. Sci. Eng. , vol.2 , Issue.6 , pp. 405-411
    • Mahesh, V.1    Kandaswamy, A.2    Vimal, C.3    Sathish, B.4
  • 127
    • 55549083887 scopus 로고    scopus 로고
    • A new arrhythmia clustering technique based on ant colony optimization
    • [127] Korürek, M., Nizam, A., A new arrhythmia clustering technique based on ant colony optimization. J. Biomed. Inform. 41:6 (2008), 874–881.
    • (2008) J. Biomed. Inform. , vol.41 , Issue.6 , pp. 874-881
    • Korürek, M.1    Nizam, A.2
  • 128
    • 79951577719 scopus 로고    scopus 로고
    • Robust multiple cardiac arrhythmia detection through bispectrum analysis
    • [128] Lanatá, A., Valenza, G., Mancuso, C., Scilingo, E.P., Robust multiple cardiac arrhythmia detection through bispectrum analysis. Expert Syst. Appl. 38:6 (2011), 6798–6804.
    • (2011) Expert Syst. Appl. , vol.38 , Issue.6 , pp. 6798-6804
    • Lanatá, A.1    Valenza, G.2    Mancuso, C.3    Scilingo, E.P.4
  • 130
    • 78651294041 scopus 로고    scopus 로고
    • Diagnosis of cardiovascular abnormalities from compressed ECG: a data mining-based approach
    • [130] Sufi, F., Khalil, I., Diagnosis of cardiovascular abnormalities from compressed ECG: a data mining-based approach. IEEE Trans. Inf. Technol. Biomed. 15:1 (2011), 33–39.
    • (2011) IEEE Trans. Inf. Technol. Biomed. , vol.15 , Issue.1 , pp. 33-39
    • Sufi, F.1    Khalil, I.2
  • 131
    • 81855218739 scopus 로고    scopus 로고
    • Analyzing ECG for cardiac arrhythmia using cluster analysis
    • [131] Yeh, Y.-C., Chiou, C.W., Lin, H.-J., Analyzing ECG for cardiac arrhythmia using cluster analysis. Expert Syst. Appl. 39:1 (2012), 1000–1010.
    • (2012) Expert Syst. Appl. , vol.39 , Issue.1 , pp. 1000-1010
    • Yeh, Y.-C.1    Chiou, C.W.2    Lin, H.-J.3
  • 132
    • 0025483033 scopus 로고
    • An approach to cardiac arrhythmia analysis using hidden markov models
    • [132] Coast, D.A., Stern, R.M., Cano, G.G., Briller, S.A., An approach to cardiac arrhythmia analysis using hidden markov models. IEEE Trans. Biomed. Eng. 37:9 (1990), 826–836.
    • (1990) IEEE Trans. Biomed. Eng. , vol.37 , Issue.9 , pp. 826-836
    • Coast, D.A.1    Stern, R.M.2    Cano, G.G.3    Briller, S.A.4
  • 135
    • 0036945755 scopus 로고    scopus 로고
    • Arrhythmia classification using the RR-interval duration signal
    • [135] Tsipouras, M.G., Fotiadis, D.I., Sideris, D., Arrhythmia classification using the RR-interval duration signal. Comput. Cardiol., 2002, 485–488.
    • (2002) Comput. Cardiol. , pp. 485-488
    • Tsipouras, M.G.1    Fotiadis, D.I.2    Sideris, D.3
  • 136
    • 35548994953 scopus 로고    scopus 로고
    • A framework for fuzzy expert system creation-application to cardiovascular diseases
    • [136] Tsipouras, M.G., Voglis, C., Fotiadis, D.I., A framework for fuzzy expert system creation-application to cardiovascular diseases. IEEE Trans. Biomed. Eng. 54:11 (2007), 2089–2105.
    • (2007) IEEE Trans. Biomed. Eng. , vol.54 , Issue.11 , pp. 2089-2105
    • Tsipouras, M.G.1    Voglis, C.2    Fotiadis, D.I.3
  • 137
    • 45749119160 scopus 로고    scopus 로고
    • Robust electrocardiogram (ECG) beat classification using discrete wavelet transform
    • [137] Minhas, F.A., Arif, M., Robust electrocardiogram (ECG) beat classification using discrete wavelet transform. Physiol. Meas. 29:5 (2008), 555–570.
    • (2008) Physiol. Meas. , vol.29 , Issue.5 , pp. 555-570
    • Minhas, F.A.1    Arif, M.2
  • 139
    • 33845864226 scopus 로고    scopus 로고
    • A patient-adapting heartbeat classifier using ECG morphology and heartbeat interval features
    • [139] de Chazal, P., Reilly, R.B., A patient-adapting heartbeat classifier using ECG morphology and heartbeat interval features. IEEE Trans. Biomed. Eng. 53:12 (2006), 2535–2543.
    • (2006) IEEE Trans. Biomed. Eng. , vol.53 , Issue.12 , pp. 2535-2543
    • de Chazal, P.1    Reilly, R.B.2
  • 140
    • 84860011372 scopus 로고    scopus 로고
    • Analysis of a semiautomatic algorithm for ECG heartbeat classification
    • [140] Llamedo, M., Martinez, J.P., Analysis of a semiautomatic algorithm for ECG heartbeat classification. Comput. Cardiol., 2011, 137–140.
    • (2011) Comput. Cardiol. , pp. 137-140
    • Llamedo, M.1    Martinez, J.P.2
  • 141
    • 70349227947 scopus 로고    scopus 로고
    • The application of hidden markov models in speech recognition
    • [141] Gales, M., Young, S., The application of hidden markov models in speech recognition. Found. Trend Signal Process. 1:3 (2007), 195–304.
    • (2007) Found. Trend Signal Process. , vol.1 , Issue.3 , pp. 195-304
    • Gales, M.1    Young, S.2
  • 142
    • 0024610919 scopus 로고
    • A tutorial on hidden markov models and selected applications in speech recognition
    • [142] Rabiner, L.R., A tutorial on hidden markov models and selected applications in speech recognition. Proc. IEEE 77:2 (1989), 257–286.
    • (1989) Proc. IEEE , vol.77 , Issue.2 , pp. 257-286
    • Rabiner, L.R.1
  • 143
    • 33746630271 scopus 로고    scopus 로고
    • ECG signal analysis through hidden markov models
    • [143] Andreao, R.V., Dorizzi, B., Boudy, J., ECG signal analysis through hidden markov models. IEEE Trans. Biomed. Eng. 53:8 (2006), 1541–1549.
    • (2006) IEEE Trans. Biomed. Eng. , vol.53 , Issue.8 , pp. 1541-1549
    • Andreao, R.V.1    Dorizzi, B.2    Boudy, J.3
  • 144
    • 0003024008 scopus 로고
    • On the handling in decision tree of continuous-valued attributes generation
    • [144] Fayyad, U.M., Irani, K.B., On the handling in decision tree of continuous-valued attributes generation. Mach. Learn. 8 (1992), 87–102.
    • (1992) Mach. Learn. , vol.8 , pp. 87-102
    • Fayyad, U.M.1    Irani, K.B.2
  • 145
    • 0029678894 scopus 로고    scopus 로고
    • Improved use of continuous attributes in c4.5
    • [145] Quinlan, J.R., Improved use of continuous attributes in c4.5. J. Artif. Intell. Res. 4 (1996), 77–90.
    • (1996) J. Artif. Intell. Res. , vol.4 , pp. 77-90
    • Quinlan, J.R.1
  • 146
    • 33744584654 scopus 로고
    • Induction of decision trees
    • [146] Quinlan, J.R., Induction of decision trees. Mach. Learn. 1 (1986), 81–106.
    • (1986) Mach. Learn. , vol.1 , pp. 81-106
    • Quinlan, J.R.1
  • 147
    • 84892841703 scopus 로고    scopus 로고
    • Evaluation of bagging ensemble method with time-domain feature extraction for diagnosing of arrhythmia beats
    • [147] Mert, A., Kılıç, N., Akan, A., Evaluation of bagging ensemble method with time-domain feature extraction for diagnosing of arrhythmia beats. Neural Comput. Appl. 24:2 (2014), 317–326.
    • (2014) Neural Comput. Appl. , vol.24 , Issue.2 , pp. 317-326
    • Mert, A.1    Kılıç, N.2    Akan, A.3
  • 148
    • 0034953193 scopus 로고    scopus 로고
    • The impact of the MIT-BIH arrhythmia database
    • [148] Moody, G.B., Mark, R.G., The impact of the MIT-BIH arrhythmia database. IEEE Eng. Med. Biol. Mag. 20:3 (2001), 45–50.
    • (2001) IEEE Eng. Med. Biol. Mag. , vol.20 , Issue.3 , pp. 45-50
    • Moody, G.B.1    Mark, R.G.2
  • 149
    • 0026705255 scopus 로고
    • The european ST-T database: standard for evaluating systems for the analysis of ST-T changes in ambulatory electrocardiography
    • [149] Taddei, A., Distante, G., Emdin, M., Moody, P.G.B., Zeelenberg, C., Marchesi, C., The european ST-T database: standard for evaluating systems for the analysis of ST-T changes in ambulatory electrocardiography. Eur. Heart J. 13 (1992), 1164–1172.
    • (1992) Eur. Heart J. , vol.13 , pp. 1164-1172
    • Taddei, A.1    Distante, G.2    Emdin, M.3    Moody, P.G.B.4    Zeelenberg, C.5    Marchesi, C.6
  • 150
  • 151
    • 0021642397 scopus 로고
    • A noise stress test for arrhythmia detectors
    • [151] Moody, G.B., Muldrow, W.E., Mark, R.G., A noise stress test for arrhythmia detectors. Comput. Cardiol. 11 (1984), 381–384.
    • (1984) Comput. Cardiol. , vol.11 , pp. 381-384
    • Moody, G.B.1    Muldrow, W.E.2    Mark, R.G.3
  • 152
    • 0029861576 scopus 로고    scopus 로고
    • A robust sequential detection algorithm for cardiac arrhythmia classification
    • [152] Chen, S.-W., Clarkson, P.M., Fan, Q., A robust sequential detection algorithm for cardiac arrhythmia classification. IEEE Trans. Biomed. Eng. 43:11 (1996), 1120–1124.
    • (1996) IEEE Trans. Biomed. Eng. , vol.43 , Issue.11 , pp. 1120-1124
    • Chen, S.-W.1    Clarkson, P.M.2    Fan, Q.3
  • 154
    • 34047269242 scopus 로고    scopus 로고
    • ECG beats classification using multiclass support vector machines with error correcting output codes
    • [154] Übeyli, E.D., ECG beats classification using multiclass support vector machines with error correcting output codes. Digit. Signal Process. 17:3 (2007), 675–684.
    • (2007) Digit. Signal Process. , vol.17 , Issue.3 , pp. 675-684
    • Übeyli, E.D.1
  • 155
    • 84984863099 scopus 로고    scopus 로고
    • Heart beat classification using particle swarm optimization
    • [155] Khazaee, A., Heart beat classification using particle swarm optimization. Int. J. Intell. Syst. Appl., 5(6), 2013, 25.
    • (2013) Int. J. Intell. Syst. Appl. , vol.5 , Issue.6 , pp. 25
    • Khazaee, A.1
  • 156
    • 85027948668 scopus 로고    scopus 로고
    • Hybrid classification engine for cardiac arrhythmia cloud service in elderly healthcare management
    • [156] Chen, H., Cheng, B.-C., Liao, G.-T., Kuo, T.-C., Hybrid classification engine for cardiac arrhythmia cloud service in elderly healthcare management. J. Vis. Lang. Comput. 25:6 (2014), 745–753.
    • (2014) J. Vis. Lang. Comput. , vol.25 , Issue.6 , pp. 745-753
    • Chen, H.1    Cheng, B.-C.2    Liao, G.-T.3    Kuo, T.-C.4
  • 158
    • 84907811194 scopus 로고    scopus 로고
    • Multiple neural network integration using a binary decision tree to improve the ECG signal recognition accuracy
    • [158] Tran, H.L., Pham, V.N., Vuong, H.N., Multiple neural network integration using a binary decision tree to improve the ECG signal recognition accuracy. Int. J. Appl. Math. Comput. Sci. 24:3 (2014), 647–655.
    • (2014) Int. J. Appl. Math. Comput. Sci. , vol.24 , Issue.3 , pp. 647-655
    • Tran, H.L.1    Pham, V.N.2    Vuong, H.N.3
  • 159
    • 84922265438 scopus 로고    scopus 로고
    • Effect of multiscale pca de-noising in ECG beat classification for diagnosis of cardiovascular diseases
    • [159] Alickovic, E., Subasi, A., Effect of multiscale pca de-noising in ECG beat classification for diagnosis of cardiovascular diseases. Circuit Syst. Signal Process. 34:2 (2015), 513–533.
    • (2015) Circuit Syst. Signal Process. , vol.34 , Issue.2 , pp. 513-533
    • Alickovic, E.1    Subasi, A.2
  • 162
    • 84931468780 scopus 로고    scopus 로고
    • Heartbeat classification system using adaptive learning from selected beats
    • [162] de Chazal, P., Heartbeat classification system using adaptive learning from selected beats. Computing in Cardiology Conference (CinC), 2014, 2014, 729–732.
    • (2014) Computing in Cardiology Conference (CinC), 2014 , pp. 729-732
    • de Chazal, P.1
  • 163
    • 84978069180 scopus 로고    scopus 로고
    • Real-time patient-specific ECG classification by 1D convolutional neural networks
    • (in press)
    • [163] Kiranyaz, S., Ince, T., Gabbouj, M., Real-time patient-specific ECG classification by 1D convolutional neural networks. IEEE Trans. Biomed. Eng., 2015, 1–12 (in press).
    • (2015) IEEE Trans. Biomed. Eng. , pp. 1-12
    • Kiranyaz, S.1    Ince, T.2    Gabbouj, M.3


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