Computer aided diagnosis of atrial arrhythmia using dimensionality reduction methods on transform domain representation

Biomedical Signal Processing and Control

Volumn 13, Issue 1, 2014, Pages 295-305

  Martis, Roshan Joy ^a   Acharya, U Rajendra ^a,b   Adeli, Hojjat ^d   Prasad, Hari ^e   Tan, Jen Hong ^a   Chua, Kuang Chua ^a   Too, Chea Loon ^c   Yeo, Sharon Wan Jie ^c   Tong, Louis ^c,f,g,h  

^a DEPARTMENT OF ELECTRONICS AND COMPUTER ENGINEERING   (Singapore)

^b UNIVERSITY OF MALAYA   (Malaysia)

^c SINGAPORE EYE RESEARCH INSTITUTE   (Singapore)

^d OHIO STATE UNIVERSITY   (United States)

^e JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

^f SINGAPORE NATIONAL EYE CENTRE   (Singapore)

^g DUKE NUS MEDICAL SCHOOL   (Singapore)

^h NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Atrial fibrillation; Atrial flutter; Discrete cosine transform; Discrete wavelet transform; Electrocardiogram; Independent component analysis; K Nearest neighbor; Principal component analysis

Indexed keywords

COMPUTER AIDED DIAGNOSIS; DECISION TREES; DIMENSIONALITY REDUCTION; DISCRETE WAVELET TRANSFORMS; DISEASES; ELECTROCARDIOGRAPHY; FLUTTER (AERODYNAMICS); HEART; IMAGE CODING; INDEPENDENT COMPONENT ANALYSIS; INTEGRATED CIRCUITS; MOTION COMPENSATION; NEAREST NEIGHBOR SEARCH; PRINCIPAL COMPONENT ANALYSIS; SIGNAL RECONSTRUCTION;

ATRIAL FIBRILLATION; ATRIAL FLUTTER; AUTOMATED DIAGNOSIS SYSTEM; COMPUTER AIDED DIAGNOSIS(CAD); DIMENSIONALITY REDUCTION METHOD; DISCRETE COSINE TRANSFORM COEFFICIENTS; K NEAREST NEIGHBOR (KNN); K-NEAREST NEIGHBORS; CLASSIFICATION TECHNIQUE;

DISCRETE COSINE TRANSFORMS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATION; COMPUTER AIDED DESIGN; COMPUTER AIDED DIAGNOSIS; DECISION TREE; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; ELECTROCARDIOGRAM; HEART ATRIUM ARRHYTHMIA; HEART ATRIUM FIBRILLATION; HUMAN; PRIORITY JOURNAL; QRS COMPLEX; RELIABILITY; SENSITIVITY AND SPECIFICITY; COMPUTER ASSISTED DIAGNOSIS; DISCRETE COSINE TRANSFORM; DISCRETE WAVELET TRANSFORM; ELECTROCARDIOGRAPHY; HEART ATRIUM FLUTTER; HEART VENTRICLE EXTRASYSTOLE; HEART VENTRICLE FIBRILLATION; HEART VENTRICLE FLUTTER; HEART VENTRICLE TACHYCARDIA; INDEPENDENT COMPONENT ANALYSIS; K NEAREST NEIGHBOR; MACHINE LEARNING; PRINCIPAL COMPONENT ANALYSIS; RR INTERVAL; SUPRAVENTRICULAR TACHYCARDIA;

EID: 84904171065     PISSN: 17468094     EISSN: 17468108     Source Type: Journal    
DOI: 10.1016/j.bspc.2014.04.001     Document Type: Article

References (94)

1. E.J. Benjamin et al. Independent risk factors for atrial fibrillation in a population-based cohort J. Am. Med. Assoc. 271 11 1994 840 844
2. A.J. Camm, I. Savelieva, S. Bharati, B.D. Lindsay, S. Nattel, K. Shinagawaa, and S.-A. Chen Atrial tachycardia, flutter, and fibrillation S. Saksena, A.J. Camm, P.A. Boyden, P. Dorian, N. Goldschlager, Electrophysiological Disorders of the Heart, Elsevier Health Sciences 2005 Churchill Livingstone Philadelphia 283 363 (chapter 15)
3. D.M. Lloyd-Jones, T.J. Wang, E.P. Leip, M.G. Larson, D. Levy, R.S. Vasan, R.B. D'Agostino, J.M. Massaro, A. Beiser, P.A. Wolf, and E.J. Benjamin Lifetime risk for development of atrial fibrillation: the Framingham heart study Circulation 110 August (9) 2004 1042 1046 (Pubitemid 39319000)
4. R.G. Hart, and L.A. Pearce Current status of stroke risk stratification in patients with atrial fibrillation Stroke 40 July (7) 2009 2607 2610
5. M. Stridh, L. Sornmo, C.J. Meurling, and S.B. Olsson Characterization of atrial fibrillation using the surface ECG: time-dependent spectral properties IEEE Trans. Biomed. Eng. 48 2001 19 27 (Pubitemid 32165707)
6. C. Vasquez, A. Hernandez, F. Mora, G. Carrault, and G. Passariello Atrial activity enhancement by Wiener filtering using an artificial neural network IEEE Trans. Biomed. Eng. 48 2001 940 944 (Pubitemid 32703047)
7. R. Mehra, P. Ziegler, S. Sarkar, D. Ritscher, and E. Warman Management of atrial tachyarrhythmias IEEE Eng. Med. Biol. Mag. 25 2006 52 62
8. M. Stridh, A. Bollmann, S.B. Olsson, and L. Sornmo Detection and feature extraction of atrial tachyarrhythmias IEEE Eng. Med. Biol. Mag. 25 2006 31 39
9. F. Sandberg, M. Stridh, and L. Sornmo Frequency tracking of atrial fibrillation using hidden Markov models IEEE Trans. Biomed. Eng. 55 2008 502 511
10. M. de la Salud Guillem, A. Bollmann, A.M. Climent, D. Husser, J. Millet-Roig, and F. Castells How many leads are necessary for a reliable reconstruction of surface potentials during atrial fibrillation? IEEE Trans. Inform. Technol. Biomed. 13 2009 330 340
11. L. Jinseok, B.A. Reyes, D.D. McManus, O. Mathias, and K.H. Chon Atrial fibrillation detection using an iPhone 4S IEEE Trans. Biomed. Eng. 60 2013 203 206
12. R.J. Martis, C. Chakraborty, and A.K. Ray A two-stage mechanism for registration and classification of ECG using Gaussian mixture model Pattern Recogn. 42 November (11) 2009 2979 2988
13. R.J. Martis, U.R. Acharya, K.M. Mandana, A.K. Ray, and C. Chakraborty Application of principal component analysis to ECG signals for automated diagnosis of cardiac health Expert Syst. Appl. 39 2012 11792 11800
14. R.J. Martis, U.R. Acharya, K.M. Mandana, A.K. Ray, and C. Chakraborty Cardiac decision making using higher order spectra Biomed. Signal Process. Control 8 2013 193 203
15. R.J. Martis, U.R. Acharya, L.C. Min, K. Mandana, A. Ray, and C. Chakraborty Application of higher order cumulant features for cardiac health diagnosis using ECG signals Int. J. Neural Syst. 23 4 2013 1350014 (19 pp.)
16. R.J. Martis, U.R. Acharya, and L.C. Min ECG beat classification using PCA, LDA, ICA and discrete wavelet transform Biomed. Signal Process. Control 8 September (5) 2013 437 448
17. R.J. Martis, U.R. Acharya, C.M. Lim, and J.S. Suri Characterization of ECG beats from cardiac arrhythmia using discrete cosine transform in PCA framework Knowl. Based Syst. 45 June 2013 76 82
18. R.J. Martis, H. Prasad, C. Chakraborty, and A.K. Ray Automated detection of atrial flutter and fibrillation using ECG signals in wavelet framework J. Mech. Med. Biol. 12 2012 1240023
19. H. Prasad, R.J. Martis, U.R. Acharya, L.C. Min, and J.S. Suri Application of higher order spectra for accurate delineation of atrial arrhythmia 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 3-7 July 2013 2013 57 60
20. A.L. Goldberger, L.A. Amaral, L. Glass, J.M. Hausdorff, P.C. Ivanov, R.G. Mark, J.E. Mietus, G.B. Moody, C.-K. Peng, and H.E. Stanley PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals Circulation 101 2000 pe215 pe222
21. G.B. Moody, and R.G. Mark The impact of the MIT-BIH arrhythmia database IEEE Eng. Med. Biol. Mag. 20 2001 45 50 (Pubitemid 32606302)
22. G.B. Moody, and R.G. Mark A new method for detecting atrial fibrillation using RR intervals Comput. Cardiol. 10 1983 227 230
23. R.J. Martis, H. Prasad, U.R. Acharya, and C.M. Lim Application of higher order spectra for accurate delineation of atrial arrhythmia Proc. Annu. Int. Conf. IEEE EMBS 2013 57 60
24. R.J. Martis, U.R. Acharya, A.K. Ray, and C. Chakraborty Application of higher order cumulants to ECG signals for the cardiac health diagnosis 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC Aug. 30 2011-Sept. 3 2011 2011 1697 1700
25. J. Pan, and W.J. Tompkins A real-time QRS detection algorithm IEEE Trans. Biomed. Eng. BME-32 3 1985 230 236 (Pubitemid 15148852)
26. J.G. Proakis Digital Signal Processing: Principles, Algorithms, and Applications 4th ed. 2007 Pearson Education India
27. A.V. Oppenheim, R.W. Schafer, and J.R. Buck Discrete-time Signal Processing vol. 5 1999 Prentice Hall Upper Saddle River
28. G. Strang Wavelets and Filter Banks 1996 Cambridge Press Wellesley
29. M. Vetterli, and C. Herley Wavelets and filter banks: theory and design IEEE Trans. Signal Process. 40 9 1992 2207 2232 (Pubitemid 23562498)
30. P.S. Addison The Illustrated Wavelet Transform Handbook: Introductory Theory and Applications in Science, Engineering, Medicine and Finance 2010 Institute of Physics London
31. N. Ahmed, T. Natarajan, and K.R. Rao Discrete cosine transform IEEE Trans. Comput. 100 1 1974 90 93
32. R.O. Duda, P.E. Hart, and D.G. Stork Pattern Classification 2012 John Wiley & Sons New York
33. A.R. Webb Statistical Pattern Recognition 2002 John Wiley and Sons Ltd West Sussex
34. K. Fukunaga Introduction to Statistical Pattern Recognition 1990 Academic Press San Diego
35. A. Hyvärinen, and O. Erkki Independent component analysis: algorithms and applications Neural Netw. 13 4 2000 411 430 (Pubitemid 30447427)
36. A. Hyvärinen, and O. Erkki A fast fixed-point algorithm for independent component analysis Neural Comput. 9 7 1997 1483 1492 (Pubitemid 127462801)
37. O. Erikki, and A. Hyvarinen Independent component analysis: algorithms and applications Neural Netw. 13 4-5 2000 411 430 (Pubitemid 30447427)
38. C.M. Bishop, and M. Nasser Nasrabadi. Pattern Recognition and Machine Learning vol. 1 2006 Springer New York
39. C.M. Bishop Neural networks for pattern recognition 1995 Oxford university press
40. S. Cerutti, L.T. Mainardi, A. Porta, and A.M. Bianchi Analysis of the dynamics of RR interval series for the detection of atrial fibrillation episodes Comput. Cardiol. 24 1997 77 80
41. J. Slocum, A. Sahakian, and S. Swiryn Diagnosis of atrial fibrillation from surface electrocardiograms based on computer-detected atrial activity J. Electrocardiol. 25 1992 1 8
42. W. Yang, Z. Yi-Sheng, N.V. Thakor, and X. Yu-Hong A short-time multifractal approach for arrhythmia detection based on fuzzy neural network IEEE Trans. Biomed. Eng. 48 2001 989 995 (Pubitemid 32776940)
43. S. Sarkar, D. Ritscher, and R. Mehra A detector for a chronic implantable atrial tachyarrhythmia IEEE Trans. Monitor Biomed. Eng. 55 2008 1219 1224 (Pubitemid 351301205)
44. H. Chao, Y. Shuming, C. Hang, L. Dingli, H. Fangtian, and T. Yuewen A novel method for detection of the transition between atrial fibrillation and sinus rhythm IEEE Trans. Biomed. Eng. 58 2011 1113 1119
45. S. Fahim, and I. Khalil Diagnosis of cardiovascular abnormalities from compressed ECG: a data mining-based approach IEEE Trans. Inform. Technol. Biomed. 15 2011 33 39
46. B. Logan, and J. Healey Robust detection of atrial fibrillation for a long term telemonitoring system Computers in cardiology 25-28 Sept 2005 619 622 (Pubitemid 46276738)
47. K. Tateno, and L. Glass Automatic detection of atrial fibrillation using the coefficient of variation and density histograms of RR and delta RR intervals Med. Biol. Eng. Comput. 39 2001 664 671 (Pubitemid 34065852)
48. A. Jovic, and N. Bogunovic Evaluating and comparing performance of feature combinations of heart rate variability measures for cardiac rhythm classification Biomed. Signal Process. Control 7 3 2012 245 255
49. R.J. Martis, U.R. Acharya, H. Prasad, C.K. Chua, C.M. Lim, and J.S. Suri Application of higher order statistics for atrial arrhythmia classification Biomed. Signal Process. Control 8 November (6) 2013 888 900
50. R.J. Martis, U.R. Acharya, H. Prasad, C.K. Chua, and C.M. Lim Automated detection of atrial fibrillation using Bayesian paradigm Knowl. Based Syst. 54 December 2013 269 275
51. A.S. Go et al. Heart disease and stroke statistics-2013 update a report from the American Heart Association Circulation 127 1 2013 e6 e245
52. B.-U. Kohler, C. Hennig, and R. Orglmeister The principles of software QRS detection IEEE Eng. Med. Biol. Mag. 21 January-February (1) 2002 42 57 (Pubitemid 34263918)
53. A.K. Jain Fundamentals of Digital Image Processing 1989 Prentice-Hall, Inc. England
54. Z. Sankari, and H. Adeli HeartSaver: a mobile cardiac monitoring system for auto-detection of atrial fibrillation, myocardial infarction and atrio-ventricular block Comput. Biol. Med. 41 April (4) 2011 211 220
55. R.J. Martis, U.R. Acharya, and H. Adeli Current methods in electrocardiogram characterization Comput. Biol. Med. 48 2014 133 149
56. H. Adeli, and A. Panakkat A probabilistic neural network for earthquake magnitude prediction Neural Netw. 22 2009 1018 1024
57. M. Ahmadlou, and H. Adeli Enhanced probabilistic neural network with local decision circles: a robust classifier Integr. Comput. Aided Eng. 17 3 2010 197 210
58. Z. Sankari, and H. Adeli Probabilistic neural networks for EEG-based diagnosis of Alzheimer's disease using conventional and wavelet coherence J. Neurosci. Methods 197 1 2011 165 170
59. F. Amini, N. Khanmohamadi Hazaveh, and A. Abdolahi Rad Wavelet PSO-based LQR algorithm for optimal structural control using active tuned mass dampers Comput. Aided Civil Infrastruct. Eng. 28 7 2013 542 557
60. C.M. Lin, A.B. Ting, C.F. Hsu, and C.M. Chung Adaptive control for MIMO uncertain nonlinear systems using recurrent wavelet neural network Int. J. Neural Syst. 22 1 2012 37 50
61. U.R. charya, S. Vinitha Sree, A.P.C. Alvin, and J.S. Suri Application of non-linear and wavelet based features for the automated identification of epileptic EEG signals Int. J. Neural Syst. 22 2 2012 1250002 1250014
62. W.Y. Hsu Single-trial motor imagery classification using asymmetry ratio, phase relation and wavelet-based fractal features, and their selected combination Int. J. Neural Syst. 23 2 2013 1350007 (13 pp.)
63. V.S. Kodogiannis, M. Amina, and I. Petrounias A clustering-based fuzzy-wavelet neural network model for short-term load forecasting Int. J. Neural Syst. 23 5 2013 1350024 (19 pp.)
64. H. Tao, J.M. Zain, M.M. Ahmed, A.N. Abdalla, and W. Jing A wavelet-based particle swarm optimization algorithm for digital image watermarking Integr. Comput. Aided Eng. 19 1 2012 81 91
65. J. Xiang, and M. Liang Wavelet-based detection of beam cracks using modal shape and frequency measurements Comput. Aided Civil Infrastruct. Eng. 27 6 2012 439 454
66. Y. Wang, W. Zhou, Q. Yuan, and X. Li Comparison of fractal features of ictal and interictal EEGs Int. J. Neural Syst. 23 6 2013 1350028 (11 pp.)
67. M. Ahmadlou, H. Adeli, and A. Adeli Fractality and a wavelet-chaos-neural network methodology for EEG-based diagnosis of autistic spectrum disorder J. Clin. Neurophysiol. 27 October (5) 2010 328 333
68. A. Ahmadlou, H. Adeli, and A. Adeli Fractality and a wavelet-chao methodology for EEG-based diagnosis of Alzheimer's disease Alzheimer Dis. Assoc. Disord. 25 1 2011 85 92
69. S. Ghosh-Dastidar, H. Adeli, and N. Dadmehr Principal component analysis-enhanced cosine radial basis function neural network for robust epilepsy and seizure detection IEEE Trans. Biomed. Eng. 55 2 2008 512 518
70. M. Al-Naser, and U. Soderstrom Reconstruction of occluded facial images using asymmetrical principal component analysis Integr. Comput. Aided Eng. 19 3 2012 273 283
71. X. Jiang, Z.J. Ma, and W.X. Ren Crack detection from the slope of the mode shape using complex continuous wavelet transform Comput. Aided Civil Infrastruct. Eng. 27 3 2012 187 201
72. G. Ghodrati Amiri, A. Abdolahi Rad, and M. Khorasani Generation of near-field artificial ground motions compatible with median predicted spectra using PSO-based neural network and wavelet analysis Comput. Aided Civil Infrastruct. Eng. 27 9 2012 711 730
73. M. Ahmadlou, and H. Adeli Wavelet-synchronization methodology: a new approach for EEG-based diagnosis of ADHD Clin. EEG Neurosci. 41 1 2010 1 10
74. Z. Zhou, and H. Adeli Time-frequency signal analysis of earthquake records using Mexican hat wavelets Comput. Aided Civil Infrastruct. Eng. 18 5 2003 379 389 (Pubitemid 36971726)
75. Z. Zhou, and H. Adeli Wavelet energy spectrum for time-frequency localization of earthquake energy Int. J. Imaging Syst. Technol. 13 2 2003 133 140
76. H. Kim, and H. Adeli Hybrid control of smart structures using a novel wavelet-based algorithm Comput. Aided Civil Infrastruct. Eng. 20 1 2005 7 22 (Pubitemid 40464642)
77. H. Kim, and H. Adeli Wavelet hybrid feedback-least mean square algorithm for robust control of cable-stayed bridges ASCE J. Bridge Eng. 10 2 2005 116 123 (Pubitemid 40303919)
78. A. Karim, and H. Adeli Fast automatic incident detection on urban and rural freeways using the wavelet energy algorithm ASCE J. Transp. Eng. 129 1 2003 57 68 (Pubitemid 36137746)
79. H.B. Celikoglu An approach to dynamic classification of traffic flow patterns by neural networks Comput. Aided Civil Infrastruct. Eng. 28 4 2013 273 288
80. E.I. Vlahogianni, and M.G. Karlaftis Fuzzy-entropy neural network freeway incident duration modeling with single and competing uncertainties Comput. Aided Civil Infrastruct. Eng. 28 6 2013 420 433
81. X. Zeng, and Y. Zhang Development of recurrent neural network considering temporal-spatial input dynamics for freeway travel time modeling Comput. Aided Civil Infrastruct. Eng. 28 5 2013 359 371
82. G.A. Peláez Coronado, M.R. Muñoz, J.M. Armingol, A. de la Escalera, J.J. Muñoz, W. van Bijsterveld, and J.A. Bolaño Detection and classification of road signs for automatic inventory systems using computer vision Integr. Comput. Aided Eng. 19 3 2012 285 298
83. D. Li, L. Xu, E. Goodman, Y. Xu, and Y. Wu Integrating a statistical background-foreground extraction algorithm and SVM classifier for pedestrian detection and tracking Integr. Comput. Aided Eng. 20 3 2013 201 216
84. M. Cabrerizo, M. Ayala, M. Goryawala, P. Jayakar, and M. Adjouadi A new parametric feature descriptor for the classification of epileptic and control EEG records in pediatric population Int. J. Neural Syst. 22 2 2012 1250001 12500016
85. L. Davis, B.J. Theobald, J. Lines, A. Toms, and A. Bagnall On the segmentation and classification of hand radiographs Int. J. Neural Syst. 22 5 2012 1250020
86. R. Harrison, R. Birchall, D. Mann, and W. Wang Novel consensus approaches to the reliable ranking of features for seabed imagery classification Int. J. Neural Syst. 22 6 2012 1250018 1250026
87. L.J. Herrera, C. Fernandes, A.M. Mora, D. Migotina, R. Largo, A. Guillén, and A.C. Rosa Combination of heterogeneous EEG feature extraction methods and stacked sequential learning for sleep stage classification Int. J. Neural Syst. 23 3 2013 1350012 (20 pp.)
88. P.J. Rodrguez-Bermudeza, J. Garca-Laencina, and Roca-Dorda Efficient automatic selection and combination of EEG features in least squares classifiers for motor-imagery brain computer interfaces Int. J. Neural Syst. 23 4 2013 1350015 (17 pp.)
89. L. Joshua, and K. Varghese Selection of accelerometer location on brick layers using decision trees Comput. Aided Civil Infrastruct. Eng. 28 5 2013 372 388
90. H. Adeli, and S.L. Hung Machine Learning - Neural Networks, Genetic Algorithms, and Fuzzy Systems 1995 John Wiley and Sons New York
91. H. Adeli, and H.S. Park Neurocomputing for Design Automation 1998 CRC Press Boca Raton, FL
92. H. Adeli, and X. Jiang Intelligent Infrastructure - Neural Networks, Wavelets, and Chaos Theory for Intelligent Transportation Systems and Smart Structures 2009 CRC Press, Taylor & Francis Boca Raton, FL
93. H. Adeli, and S. Ghosh-Dastidar Automated EEG-based Diagnosis of Neurological Disorders - Inventing the Future of Neurology 2010 CRC Press, Taylor & Francis Boca Raton, FL
94. N. Siddique, and H. Adeli Computational Intelligence - Synergies of Fuzzy Logic Neural Networks and Evolutionary Computing 2013 Wiley West Sussex, United Kingdom 2013