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Computer Analysis of the Electrocardiogram

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Comprehensive Electrocardiology

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References

  1. Turing, A.M., Computing machinery and intelligence. Mind, 1950;59: 433–460.

    Article  Google Scholar 

  2. Rijlant, P.B.L., L’analyse par un calculateur analogique des electrocardiogrammes scalaires et vectoriels. Bull. Acad. Royal Med. Belgique, 1962;2: 363.

    CAS  Google Scholar 

  3. Rautaharju, P.M., The impact of computers on electrocardiography. Eur. J. Cardiol., 1978;8: 237–248.

    PubMed  CAS  Google Scholar 

  4. Taback, L., E. Marden, H.L. Mason, and H. Pipberger, Digital recording of electrocardiographic data for analysis by means of a digital electronic computer. IRE Trans. Med. Electron., 1959;6: 167–171.

    Article  Google Scholar 

  5. Pipberger, H.V., R.J. Arms, and F.W. Stallmann, Automatic screening of normal and abnormal electrocardiograms by means of a digital electronic computer. Proc. Soc. Exp. Biol. Med., 1961;106: 130–132.

    PubMed  CAS  Google Scholar 

  6. Stallmann, F.W. and H.V. Pipberger, Automatic recognition of electrocardiographic waves by digital computer. Circ. Res., 1961;9: 1138–1143.

    Article  PubMed  CAS  Google Scholar 

  7. Cornfield, J., R.A. Dunn, C.D. Batchlor, and H.V. Pipberger, Multigroup diagnosis of electrocardiograms. Comput. Biomed. Res., 1973;6: 97–120.

    Article  PubMed  CAS  Google Scholar 

  8. Pipberger, H.V., D. McCaughan, D. Littmann, H.A. Pipberger, J. Cornfield, R.A. Dunn, et al., Clinical application of a second generation electrocardiographic computer program. Am. J. Cardiol., 1975;35: 597–608.

    Article  PubMed  CAS  Google Scholar 

  9. Caceres, C.A., C.A. Steinberg, S. Abraham, J. CW, J.M. McBride, and W.E. Tolles, et al., Computer extraction of electrocardiographic parameters. Circulation, 1962;25: 356–362.

    Article  PubMed  CAS  Google Scholar 

  10. Rautaharju, P.M., The current state of computer ECG analysis: a critique, in Trends in Computer-Processed Electrocardiograms, J.H. van Bemmel and J.L. Willems, Editors. Amsterdam: North-Holland, 1976, pp. 117–124.

    Google Scholar 

  11. Drazen, E.L., Use of computer-assisted ECG interpretation in the United States, in Computers in Cardiology 1979, K.L. Ripley and H.G. Ostrow, Editors. Long Beach: IEEE Comp Soc. 1979, pp. 83–85.

    Google Scholar 

  12. Drazen, E.L., N. Mann, R. Borun, M. Laks, and A. Bersen, Survey of computer-assisted electrocardiography in the United States. J. Electrocardiol., 1988;21(Suppl): S98–104.

    Article  PubMed  Google Scholar 

  13. Macfarlane, P.W., A brief history of computer-assisted electrocardiography. Methods Inf. Med., 1990;29: 272–281.

    PubMed  CAS  Google Scholar 

  14. Rautaharju, P.M., M. Ariet, T.A. Pryor, R.C. Arzbaecher, J.J. Bailey, R. Bonner, et al., The quest for optimal electrocardiography. Task force III: computers in diagnostic electrocardiography. Am. J. Cardiol., 1978;41: 158–170.

    Article  PubMed  CAS  Google Scholar 

  15. Pipberger, H.V., J. Cornfield, What ECG computer program to choose for clinical application. The need for consumer protection. Circulation, 1973;47: 918–920.

    Article  PubMed  CAS  Google Scholar 

  16. Frank, E., An accurate, clinically practical system for spatial vectorcardiography. Circulation, 1956;13: 737–749.

    Article  PubMed  CAS  Google Scholar 

  17. Rautaharju, P.M., H.W. Blackburn, H.K. Wolf, and M. Horacek, Computers in clinical electrocardiology. Is vectorcardiography becoming obsolete? Adv. Cardiol., 1976;16: 143–156.

    PubMed  CAS  Google Scholar 

  18. Dower, G.E., H.B. Machado, and J.A. Osborne, On deriving the electrocardiogram from vectoradiographic leads. Clin. Cardiol., 1980;3: 87–95.

    PubMed  CAS  Google Scholar 

  19. Edenbrandt, L. and O. Pahlm, Vectorcardiogram synthesized from a 12-lead ECG: superiority of the inverse Dower matrix. J. Electrocardiol., 1988;21: 361–367.

    Article  PubMed  CAS  Google Scholar 

  20. Rubel, P., I. Benhadid, and J. Fayn, Quantitative assessment of eight different methods for synthesizing Frank VCGs from simultaneously recorded standard ECG leads. J. Electrocardiol., 1992;24(Suppl): 197–202.

    Article  PubMed  Google Scholar 

  21. Macfarlane, P.W., M.P. Watts, and T.D.V. Lawrie, Hybrid electrocardiography, in Optimization of Computer ECG Processing, H.K. Wolf and P.W. Macfarlane, Editors. Amsterdam: North-Holland, 1980, pp. 57–61.

    Google Scholar 

  22. Kornreich, F. and P.M. Rautaharju, The missing waveform and diagnostic information in the standard 12 lead electrocardiogram. J. Electrocardiol., 1981;14: 341–350.

    Article  PubMed  CAS  Google Scholar 

  23. Kornreich, F., The missing waveform information in the orthogonal electrocardiogram (Frank leads). I. Where and how can this missing waveform information be retrieved? Circulation, 1973;48: 984–995.

    Article  PubMed  CAS  Google Scholar 

  24. Kornreich, F., P. Smets, and J. Kornreich, About challenging the uniqueness of a new, so-called “optimal”, “total” or “maximal” 9-lead system, in Trends in Computer-Processed Electrocardiograms, J.H. van Bemmel and J.L. Willems, Editors. Amsterdam: North-Holland, 1977, pp. 293–301.

    Google Scholar 

  25. Kornreich, F., R.L. Lux, and R.S. MacLeod, Map representation and diagnostic performance of the standard 12-lead ECG. J. Electrocardiol., 1995;28(Suppl): 121–123.

    Article  PubMed  Google Scholar 

  26. Kors, J.A. and G. van Herpen, How many electrodes and where? A “poldermodel” for electrocardiography. J. Electrocardiol., 2002;35(Suppl): 7–12.

    Article  PubMed  Google Scholar 

  27. Nelwan, S.P., J.A. Kors, S.H. Meij, J.H. van Bemmel, and M.L. Simoons, Reconstruction of the 12-lead electrocardiogram from reduced lead sets. J. Electrocardiol., 2004;37: 11–18.

    Article  PubMed  Google Scholar 

  28. Dower, G.E., A. Yakush, S.B. Nazzal, R.V. Jutzy, and C.E. Ruiz, Deriving the 12-lead electrocardiogram from four (EASI) electrodes. J. Electrocardiol., 1988;21(Suppl): S182–S187.

    Article  PubMed  Google Scholar 

  29. Burger, H.C. and J.B. Van Milaan, Heart-vector and leads. Brit. Heart J., 1946;8: 157–161.

    Article  Google Scholar 

  30. Mortara, D.W., Source consistency filtering. Application to resting ECGs. J. Electrocardiol., 1992;25(Suppl): 200–206.

    Article  PubMed  Google Scholar 

  31. Kors, J.A. and G. van Herpen, Accurate automatic detection of electrode interchange in the electrocardiogram. Am. J. Cardiol., 2001;88: 396–399.

    Article  PubMed  CAS  Google Scholar 

  32. Burger, H.C., A. van Brummelen, and G. van Herpen, Compromise in vectorcardiography. II. Alterations of coefficients as a means of adapting one lead system to another. Subjective and mathematical comparison of four systems of VCG. Am. Heart J., 1962;64: 666–678.

    Article  PubMed  CAS  Google Scholar 

  33. Surawicz, B., H. Uhley, R. Borun, M. Laks, L. Crevasse, K. Rosen, et al., The quest for optimal electrocardiography. Task force I: standardization of terminology and interpretation. Am. J. Cardiol., 1978;41: 130–145.

    Article  PubMed  CAS  Google Scholar 

  34. The CSE Working Party, Recommendations for measurement standards in quantitative electrocardiography. Eur. Heart J., 1985;6: 815–825.

    Google Scholar 

  35. Willems, J.L., E.O. Robles de Medina, R. Bernard, P. Coumel, C. Fisch, D. Krikler, et al., Criteria for intraventricular conduction disturbances and pre-excitation. World Health Organizational/International Society and Federation for Cardiology Task Force Ad Hoc. J. Am. Coll. Cardiol., 1985;5: 1261–1275.

    Article  PubMed  CAS  Google Scholar 

  36. Kadish, A.H., A.E. Buxton, H.L. Kennedy, B.P. Knight, J.W. Mason, C.D. Schuger, et al., ACC/AHA clinical competence statement on electrocardiography and ambulatory electrocardiography: A report of the ACC/AHA/ACP-ASIM task force on clinical competence. Circulation, 2001;104: 3169– 3178.

    PubMed  CAS  Google Scholar 

  37. van Bemmel, J.H., J.A. Kors, and G. van Herpen, Methodology of the modular ECG analysis system MEANS. Methods Inf. Med., 1990;29: 346–353.

    PubMed  Google Scholar 

  38. Talmon, J.L. and J.H. van Bemmel, The advantage of modular software design in computerized ECG analysis. Med. Inform., 1986;11: 117–128.

    Article  CAS  Google Scholar 

  39. Willems, J.L. and J. Pardaens, Differences in measurement results obtained by four different ECG computer programs, in Computers in Cardiology 1977, H.G. Ostrow and K.L. Ripley, Editors. Long Beach: IEEE Comput Soc, 1977, pp. 115–121.

    Google Scholar 

  40. Willems, J.L., A plea for common standards in computer aided ECG analysis. Comput. Biomed. Res., 1980;13: 120–131.

    Article  PubMed  CAS  Google Scholar 

  41. Pipberger, H.V., Comparative evaluation of electrocardiography computer programs, in Computers in Cardiology 1976, H.G. Ostrow and K.L. Ripley, Editors. Long Beach: IEEE Computer Society, 1976, pp. 85–88.

    Google Scholar 

  42. Crevasse, L. and M.A. Ariet, New scalar electrocardiographic computer program. Clinical evaluation. JAMA, 1973;226: 1089–1093.

    Article  PubMed  CAS  Google Scholar 

  43. Romhilt, D.W. and E.H. Estes, A point-score system for the ECG diagnosis of left ventricular hypertrophy. Am. Heart J., 1968;75: 752–758.

    Article  PubMed  CAS  Google Scholar 

  44. Bailey, J.J., S.B. Itscoitz, J.W. Hirshfeld, L.E. Grauer, and M.R.A. Horton, Method for evaluating computer programs for electrocardiographic interpretation. I. Application to the experimental IBM program of 1971. Circulation, 1974;50: 73–79.

    Article  PubMed  CAS  Google Scholar 

  45. Bailey, J.J., S.B. Itscoitz, L.E. Grauer, J.W. Hirshfeld, and M.R.A. Horton, Method for evaluating computer programs for electrocardiographic interpretation. II. Application to version D of the PHS program and the Mayo clinic program of 1968. Circulation, 1974;50: 80–87.

    Article  PubMed  CAS  Google Scholar 

  46. Hodges, M., A clinical evaluation of the H-P ECG analysis program: program accuracy and value of adjustable criteria, in Computers in Cardiology 1979, K.L. Ripley and H.G. Ostrow, Editors. Long Beach: IEEE Comput Soc, 1979, pp. 167–170.

    Google Scholar 

  47. Garcia, R., G.M. Breneman, and S. Goldstein, Electrocardiogram computer analysis. Practical value of the IBM Bonner-2 (V2 MO) program. J. Electrocardiol., 1981;14: 283–288.

    Article  PubMed  CAS  Google Scholar 

  48. Caceres, C.A. and H.M. Hochberg, Performance of the computer and physician in the analysis of the electrocardiogram. Am. Heart J., 1970;79: 439–443.

    Article  PubMed  CAS  Google Scholar 

  49. Bourdillon, P.J. and D. Kilpatrick, Clinicians, the Mount Sinai program and the Veterans’ Administration program evaluated against clinico-pathological data derived independently of the electrocardiogram. Eur. J. Cardiol., 1978;8: 395–412.

    PubMed  CAS  Google Scholar 

  50. Willems, J.L., H. Ector, J. Pardaens, J. Piessens, and H. de Geest, Computer and conventional ECG analysis: correlation with cineangiographic data. Adv. Cardiol., 1978;21: 177–180.

    PubMed  CAS  Google Scholar 

  51. Khadr, N.E., C.L. Bray, D.C. Beton, R.S. Croxson, M. Hughes, C. Jeffery, et al., Diagnosis of left ventricular hypertrophy and myocardial infarction by Bonner/IBM program verified by ECG-independent evidence, in Computers in Cardiology, K.L. Ripley and H.G. Ostrow, Editors. Long Beach: IEEE Comput Soc, 1979, pp. 93–97.

    Google Scholar 

  52. Macfarlane, P.W., D.I. Melville, M.R. Horton, and J.J. Bailey, Comparative evaluation of the IBM (12-lead) and Royal Infirmary (orthogonal three-lead) ECG computer programs. Circulation, 1981;63: 354–359.

    Article  PubMed  CAS  Google Scholar 

  53. Willems, J.L., E. Lesaffre, and J. Pardaens, Comparison of the classification ability of the electrocardiogram and vectorcardiogram. Am. J. Cardiol., 1987;59: 119–124.

    Article  PubMed  CAS  Google Scholar 

  54. Zywietz, C. and B. Schneider, Editors. Computer Application in ECG and VCG Analysis. Amsterdam: North-Holland, 1973.

    Google Scholar 

  55. van Bemmel, J.H. and J.L. Willems, Editors. Trends in Computer-Processed Electrocardiograms. Amsterdam: North-Holland, 1977.

    Google Scholar 

  56. Wolf, H.K. and P.W. Macfarlane, Editors. Optimization of Computer ECG Processing. Amsterdam: North-Holland, 1980.

    Google Scholar 

  57. Willems, J.L., P. Arnaud, R. Degani, P.W. Macfarlane, J.H. van Bemmel, and C. Zywietz, Protocol for the Concerted Action Project “Common Standards for Quantitative Electrocardiography”. Leuven: ACCO, 1980.

    Google Scholar 

  58. The CSE European Working Party, An approach to measurement standards in computer ECG analysis, in Optimization of Computer ECG Processing, H.K. Wolf and P.W. Macfarlane, Editors. Amsterdam: North-Holland, 1980, pp. 135–137.

    Google Scholar 

  59. Willems, J.L., P. Arnaud, J.H. van Bemmel, R. Degani, P.W. Macfarlane, C. Zywietz, Common standards for quantitative electrocardiography: goals and main results. CSE Working Party. Methods Inf. Med., 1990;29: 263–271.

    Google Scholar 

  60. Willems, J.L., P. Arnaud, J.H. van Bemmel, P.J. Bourdillon, R. Degani, B. Denis, et al., Establishment of a reference library for evaluating computer ECG measurement programs. Comput. Biomed. Res., 1985;18: 439–457.

    Article  PubMed  CAS  Google Scholar 

  61. Willems, J.L., P. Arnaud, J.H. van Bemmel, P.J. Bourdillon, R. Degani, B. Denis, et al., A reference data base for multilead electrocardiographic computer measurement programs. J. Am. Coll. Cardiol., 1987;10: 1313–1321.

    Article  PubMed  CAS  Google Scholar 

  62. Willems, J.L., P. Arnaud, J.H. van Bemmel, P.J. Bourdillon, C. Brohet, S. Dalla Volta, et al., Assessment of the performance of electrocardiographic computer programs with the use of a reference data base. Circulation, 1985;71: 523–534.

    Article  PubMed  CAS  Google Scholar 

  63. Willems, J.L., Common Standards for Quantitative Electrocardiography. CSE Atlas. Referee Results First Phase Library – Data Set 1. Leuven: ACCO, 1983.

    Google Scholar 

  64. Willems, J.L., Common Standards for Quantitative Electrocardiography. CSE Multilead Atlas. Measurement Results – Data Set 3. Leuven: ACCO, 1988.

    Google Scholar 

  65. Willems, J.L., Common Standards for Quantitative Electrocardiography, 4th Progress Report. Leuven: ACCO, 1984.

    Google Scholar 

  66. Willems, J.L., Common Standards for Quantitative Electrocardiography, 10th Progress Report. Leuven: ACCO, 1990.

    Google Scholar 

  67. Berson, A.S., Analog-to-digital conversion, in: Computer Application on ECG and VCG Analysis, C. Zywietz and R. Schneider, Editors. Amsterdam: North-Holland, 1973, pp. 57–72.

    Google Scholar 

  68. Berson, A.S., T.A. Ferguson, C.D. Batchlor, R.A. Dunn, and H.V. Pipberger, Filtering and sampling for electrocardiographic data processing. Comput. Biomed. Res., 1977;10: 605–616.

    Article  PubMed  CAS  Google Scholar 

  69. Bailey, J.J., A.S. Berson, A. Garson, L.G. Horan, P.W. Macfarlane, D.W. Mortara, et al., Recommendations for standardization and specifications in automated electrocardiography: bandwidth and digital signal processing. A report for health professionals by an ad hoc writing group of the Committee on Electrocardiography and Cardiac Electrophysiology of the Council on Clinical Cardiology, American Heart Association. Circulation, 1990;81: 730–739.

    Article  PubMed  CAS  Google Scholar 

  70. Rijnbeek, P.R., J.A. Kors, and M. Witsenburg, Minimum bandwidth requirements for recording of pediatric electrocardiograms. Circulation, 2001;104: 3087–3090.

    Article  PubMed  CAS  Google Scholar 

  71. Hedén, B., M. Ohlsson, L. Edenbrandt, R. Rittner, O. Pahlm, and C. Peterson, Artificial neural networks for recognition of electrocardiographic lead reversal. Am. J. Cardiol., 1995;75: 929–933.

    Article  PubMed  Google Scholar 

  72. Schijvenaars, R.J., J.A. Kors, G. van Herpen, and J.H. van Bemmel, A method to reduce the effect of electrode position variations on automated ECG interpretation. J. Electrocardiol., 1995;28: 350–351.

    Article  PubMed  CAS  Google Scholar 

  73. Brodnick, D., A method to locate electrode placement. J. Electrocardiol., 2000;33(Suppl): 211–218.

    Article  PubMed  Google Scholar 

  74. McManus, C.D., K.D. Neubert, and E. Cramer, Characterization and elimination of AC noise in electrocardiograms: a comparison of digital filtering methods. Comput. Biomed. Res., 1993;26: 48–67.

    Article  PubMed  CAS  Google Scholar 

  75. Cramer, E., C.D. McManus, and D. Neubert, Estimation and removal of power line interference in the electrocardiogram: a comparison of digital approaches. Comput. Biomed. Res., 1987;20: 12–28.

    Article  PubMed  CAS  Google Scholar 

  76. Lynn, P.A., Online digital filters for biological signals: some fast designs for a small computer. Med. Biol. Eng. Comput., 1977;15: 534–540.

    Article  PubMed  CAS  Google Scholar 

  77. Weaver, C.S., J. von der Groeben, P.E. Mantey, J.G. Toole, C.A. Cole, J.W. Fitzgerald, et al., Digital filtering with applications to electrocardiogram processing. IEEE Trans. Audio Electroacoust., 1968;16: 350–391.

    Article  Google Scholar 

  78. Levkov, C., G. Michov, R. Ivanov, and I.K. Daskalov, Subtraction of 50 Hz interference from the electrocardiogram. Med. Biol. Eng. Comput., 1984;22: 371–373.

    Article  PubMed  CAS  Google Scholar 

  79. Dotsinsky, I. and T. Stoyanov, Power-line interference cancellation in ECG signals. Biomed. Instrum. Technol., 2005;39: 155–162.

    PubMed  CAS  Google Scholar 

  80. Levkov, C., G. Mihov, R. Ivanov, I. Daskalov, I. Christov, and I. Dotsinsky, Removal of power-line interference from the ECG: a review of the subtraction procedure. Biomed. Eng. Online, 2005;4: 50.

    Article  PubMed  Google Scholar 

  81. Widrow, B., J.R. Glover, M. McCool, J. Kaunitz, C.S. Williams, R.H. Hearn, et al., Adaptive noise cancelling: principles and applications. Proc. IEEE, 1975;63: 1692–1716.

    Article  Google Scholar 

  82. Glover, J.R., Adaptive noise canceling applied to sinusoidal interferences. IEEE Trans. Acoust. Speech Signal Process., 1977;25: 484–491.

    Article  Google Scholar 

  83. Thakor, N.V. and Y.S. Zhu, Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection. IEEE Trans. Biomed. Eng., 1991;38: 785–794.

    Article  PubMed  CAS  Google Scholar 

  84. Mortara, D.W., Digital filters for ECG signals, in Computers in Cardiology 1977, H.G. Ostrow and K.L. Ripley, Editors. New York: IEEE Comput Soc, 1977, pp. 511–514.

    Google Scholar 

  85. Talmon, J.L., Pattern recognition of the ECG. A structured analysis, dissertation. Amsterdam: Free University, 1983.

    Google Scholar 

  86. Ahlstrom, M.L. and W.J. Tompkins, Digital filters for real-time ECG signal processing using microprocessors. IEEE Trans. Biomed. Eng., 1985;32: 708–713.

    Article  PubMed  CAS  Google Scholar 

  87. Hamilton, P.S., A comparison of adaptive and nonadaptive filters for reduction of power line interference in the ECG. IEEE Trans. Biomed. Eng., 1996;43: 105–109.

    Article  PubMed  CAS  Google Scholar 

  88. Glover, J.R., Comments on “Digital filters for real-time ECG signal processing using microprocessors”. IEEE Trans. Biomed. Eng., 1987;34: 962–963.

    Article  PubMed  Google Scholar 

  89. Pipberger, H.V., R.C. Arzbaecher, A.S. Berson, S.A. Briller, D.A. Brody, N.C. Flowers, et al., Recommendations for standardization of leads and of specifications for instruments in electrocardiography and vectorcardiography: report of the Committee on Electrocardiography, American Heart Association. Circulation, 1975;52: 11–31.

    Google Scholar 

  90. Bailey, J.J., The triangular wave test for electrocardiographic devices: a historical perspective. J. Electrocardiol., 2004;37(Suppl): 71–73.

    Article  PubMed  Google Scholar 

  91. van Alste, J.A., W. van Eck, and O.E. Herrmann, ECG baseline wander reduction using linear phase filters. Comput. Biomed. Res., 1986;19: 417–427.

    Article  PubMed  Google Scholar 

  92. Sörnmo, L., Time-varying digital filtering of ECG baseline wander. Med. Biol. Eng. Comput., 1993;31: 503–508.

    Article  PubMed  Google Scholar 

  93. Shusterman, V., S.I. Shah, A. Beigel, and K.P. Anderson, Enhancing the precision of ECG baseline correction: selective filtering and removal of residual error. Comput Biomed Res 2000; 33:144–160.

    Article  PubMed  CAS  Google Scholar 

  94. Macfarlane, P.W., J. Peden, G. Lennox, M.P. Watts, and T.D.V. Lawrie, The Glasgow system, in Trends in Computer-Processed Electrocardiograms, J.H. van Bemmel and J.L. Willems, Editors. Amsterdam: North-Holland, 1977, pp. 143–150.

    Google Scholar 

  95. Boucheham, B., Y. Ferdi, and M.C. Batouche, Recursive versus sequential multiple error measures reduction: a curve simplification approach to ECG data compression. Comput. Methods Programs Biomed., 2005;78: 1–10.

    Article  PubMed  CAS  Google Scholar 

  96. Douglas, D.H. and T.K. Peucker, Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. Can. Cartographer, 1973;10: 112–122.

    Article  Google Scholar 

  97. Meyer, C.R. and H.N. Keiser, Electrocardiogram baseline noise estimation and removal using cubic splines and state-space computation techniques. Comput. Biomed. Res., 1977;10: 459–470.

    Article  PubMed  CAS  Google Scholar 

  98. Gradwohl, J.R., E.W. Pottala, M.R. Horton, and J.J. Bailey, Comparison of two methods for removing baseline wander in the ECG, in Computers in Cardiology 1988, K.L. Ripley, Editor. Los Angeles: IEEE Comput Soc, 1988, pp. 493–496.

    Google Scholar 

  99. Froning, J.N., M.D. Olson, and V.F. Froelicher, Problems and limitations of ECG baseline estimation and removal using a cubic spline technique during exercise ECG testing: recommendations for proper implementation. J. Electrocardiol., 1988;21(Suppl): S149–157.

    Article  PubMed  Google Scholar 

  100. Pottala, E.W., J.J. Bailey, M.R. Horton, and J.R. Gradwohl, Suppression of baseline wander in the ECG using a bilinearly transformed, null-phase filter. J. Electrocardiol., 1989;22(Suppl): 243–247.

    Article  PubMed  Google Scholar 

  101. Frankel, R.A., E.W. Pottala, R.W. Bowser, and J.J. Bailey, A filter to suppress ECG baseline wander and preserve ST-segment accuracy in a real-time environment. J. Electrocardiol., 1991;24: 315–323.

    Article  PubMed  CAS  Google Scholar 

  102. Longini, R.L., J.P. Giolma, C. Wall, and R.F. Quick, Filtering without phase shift. IEEE Trans. Biomed. Eng., 1975;22: 432–433.

    Article  PubMed  CAS  Google Scholar 

  103. de Pinto, V., Filters for the reduction of baseline wander and muscle artifact in the ECG. J. Electrocardiol., 1992;25(Suppl): 40–48.

    Article  PubMed  Google Scholar 

  104. van Alste, J.A. and T.S. Schilder, Removal of base-line wander and power-line interference from the ECG by an efficient FIR filter with a reduced number of taps. IEEE Trans. Biomed. Eng., 1985;32: 1052–1060.

    Article  PubMed  Google Scholar 

  105. Jane, R., P. Laguna, N.V. Thakor, and P. Caminal, Adaptive baseline wander removal in the ECG: comparative analysis with cubic spline technique, in Computers in Cardiology 1992, A. Murray and R.C. Arzbaecher, Editors. Los Alamitos: IEEE Comput Soc, 1992, pp. 143–146.

    Google Scholar 

  106. Laguna, P., R. Jane, O. Meste, P.W. Poon, P. Caminal, H. Rix, et al., Adaptive filter for event-related bioelectric signals using an impulse correlated reference input: comparison with signal averaging techniques. IEEE Trans. Biomed. Eng., 1992;39: 1032–1044.

    Article  PubMed  CAS  Google Scholar 

  107. Moody, G.B. and R.G. Mark, The impact of the MIT-BIH arrhythmia database. IEEE Eng. Med. Biol. Mag., 2001;20: 45–50.

    Article  PubMed  CAS  Google Scholar 

  108. Park, K.L., K.J. Lee, and H.R. Yoon, Application of a wavelet adaptive filter to minimise distortion of the ST-segment. Med. Biol. Eng. Comput., 1998;36: 581–586.

    Article  PubMed  CAS  Google Scholar 

  109. Taddei, A., G. Distante, M. Emdin, P. Pisani, G.B. Moody, C. Zeelenberg, et al., The European ST-T database: standard for evaluating systems for the analysis of ST-T changes in ambulatory electrocardiography. Eur. Heart J., 1992;13: 1164–1172.

    PubMed  CAS  Google Scholar 

  110. Chu, C.H. and E.J. Delp, Nonlinear methods in electrocardiogram signal processing. J. Electrocardiol., 1990;23(Suppl): 192–197.

    Article  PubMed  Google Scholar 

  111. Sun, Y., K. Chan, and S.M. Krishnan, ECG signal conditioning by morphological filtering. Comput. Biol. Med., 2002;32: 465–479.

    Article  PubMed  Google Scholar 

  112. Chu, C.H. and E.J. Delp, Impulsive noise suppression and background normalization of electrocardiogram signals using morphological operators. IEEE Trans. Biomed. Eng., 1989;36: 262–273.

    Article  PubMed  CAS  Google Scholar 

  113. Haralick, R.M., S.R. Sternberg, and X. Zhuang, Image analysis using mathematical morphology. IEEE Trans. Pattern Anal. Mach. Intell., 1987;9: 532–550.

    Article  PubMed  CAS  Google Scholar 

  114. Talmon, J.L., J.A. Kors, and J.H. van Bemmel, Adaptive Gaussian filtering in routine ECG/VCG analysis. IEEE Trans. Acoust. Speech Signal Process., 1986;34: 527–534.

    Article  Google Scholar 

  115. Hodson, E.K., D.R. Thayer, and C. Franklin, Adaptive Gaussian filtering and local frequency estimates using local curvature analysis. IEEE Trans. Acoust. Speech Signal Process., 1981;29: 854–859.

    Article  Google Scholar 

  116. Wei, D., E. Harasawa, and H. Hosaka, A low-distortion filter method to reject muscle noise in multi-lead electrocardiogram systems. Front Med. Biol. Eng., 1999;9: 315–330.

    PubMed  CAS  Google Scholar 

  117. Acar, B. and H. Koymen, SVD-based on-line exercise ECG signal orthogonalization. IEEE Trans. Biomed. Eng., 1999;46: 311–321.

    Article  PubMed  CAS  Google Scholar 

  118. Paul, J.S., M.R. Reddy, and V.J. Kumar, A transform domain SVD filter for suppression of muscle noise artefacts in exercise ECG’s. IEEE Trans. Biomed. Eng., 2000;47: 654–663.

    Article  PubMed  CAS  Google Scholar 

  119. Nikolaev, N., A. Gotchev, K. Egiazarian, and Z. Nikolov, Suppression of electromyogram interference on the electrocardiogram by transform domain denoising. Med. Biol. Eng. Comput., 2001;39: 649–655.

    Article  PubMed  CAS  Google Scholar 

  120. Raphisak, P., S.C. Schuckers, and A. de Jongh Curry, An algorithm for EMG noise detection in large ECG data, in Computers in Cardiology 2004, A. Murray, Editor. Piscataway, NJ: IEEE Comput Soc, 2004, pp. 369–372.

    Chapter  Google Scholar 

  121. Brohet, C.R., C. Derwael, A. Robert, and R. Fesler, Methodology of ECG interpretation in the Louvain program. Methods Inf. Med., 1990;29: 403–409.

    PubMed  CAS  Google Scholar 

  122. Willems, J.L., Common Standards for Quantitative Electrocardiography, 2nd CSE Progress Report. Leuven: ACCO, 1982.

    Google Scholar 

  123. Pipberger, H.V., C.D. McManus, and H.A. Pipberger, Methodology of ECG interpretation in the AVA program. Methods Inf. Med., 1990;29: 337–340.

    PubMed  CAS  Google Scholar 

  124. Helfenbein, E.D., J.M. Lindauer, S.H. Zhou, R.E. Gregg, and E.C. Herleikson, A software-based pacemaker pulse detection and paced rhythm classification algorithm. J. Electrocardiol., 2002;35(Suppl): 95–103.

    Article  PubMed  Google Scholar 

  125. Hamilton, P.S. and W.J. Tompkins, Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database. IEEE Trans. Biomed. Eng., 1986;33: 1157–1165.

    Article  PubMed  CAS  Google Scholar 

  126. Friesen, G.M., T.C. Jannett, M.A. Jadallah, S.L. Yates, S.R. Quint, and H.T. Nagle, A comparison of the noise sensitivity of nine QRS detection algorithms. IEEE Trans. Biomed. Eng., 1990;37: 85–98.

    Article  PubMed  CAS  Google Scholar 

  127. Hu, Y.H., W.J. Tompkins, J.L. Urrusti, and V.X. Afonso, Applications of artificial neural networks for ECG signal detection and classification. J. Electrocardiol., 1993;26(Suppl): 66–73.

    PubMed  Google Scholar 

  128. Suppappola, S. and Y. Sun, Nonlinear transforms of ECG signals for digital QRS detection: a quantitative analysis. IEEE Trans. Biomed. Eng., 1994;41: 397–400.

    Article  PubMed  CAS  Google Scholar 

  129. Afonso, V.X., W.J. Tompkins, T.Q. Nguyen, and S. Luo, ECG beat detection using filter banks. IEEE Trans. Biomed. Eng., 1999;46: 192–202.

    Article  PubMed  CAS  Google Scholar 

  130. Kohler, B.U., C. Hennig, and R. Orglmeister, The principles of software QRS detection. IEEE Eng. Med. Biol. Mag., 2002;21: 42–57.

    Article  PubMed  Google Scholar 

  131. Martinez, J.P., R. Almeida, S. Olmos, A.P. Rocha, and P. Laguna, A wavelet-based ECG delineator: evaluation on standard databases. IEEE Trans. Biomed. Eng., 2004;51: 570–581.

    Article  PubMed  Google Scholar 

  132. Pahlm, O. and L. Sörnmo, Software QRS detection in ambulatory monitoring—a review. Med. Biol. Eng. Comput., 1984;22: 289–297.

    Article  PubMed  CAS  Google Scholar 

  133. Li, C., C. Zheng, and C. Tai, Detection of ECG characteristic points using wavelet transforms. IEEE Trans. Biomed. Eng., 1995;42: 21–28.

    Article  PubMed  CAS  Google Scholar 

  134. Kadambe, S., R. Murray, and G.F. Boudreaux-Bartels, Wavelet transform-based QRS complex detector. IEEE Trans. Biomed. Eng., 1999;46: 838–848.

    Article  PubMed  CAS  Google Scholar 

  135. Vijaya, G., V. Kumar, and H.K. Verma, ANN-based QRS-complex analysis of ECG. J. Med. Eng. Technol., 1998;22: 160–167.

    Article  PubMed  CAS  Google Scholar 

  136. Poli, R., S. Cagnoni, and G. Valli, Genetic design of optimum linear and nonlinear QRS detectors. IEEE Trans. Biomed. Eng., 1995;42: 1137–1141.

    Article  PubMed  CAS  Google Scholar 

  137. Belforte, G., R. De Mori, and F. Ferraris, A contribution to the automatic processing of electrocardiograms using syntactic methods. IEEE Trans. Biomed. Eng., 1979;26: 125–136.

    Article  PubMed  CAS  Google Scholar 

  138. Papakonstantinou, G., E. Skordalakis, and F. Gritzali, An attribute grammar for QRS detection. Pattern Recog., 1986;19: 297–303.

    Article  Google Scholar 

  139. Skordalakis, E., Syntactic ECG processing: a review. Pattern Recog., 1986;19: 305–313.

    Article  Google Scholar 

  140. Kors, J.A., J.L. Talmon, and J.H. van Bemmel, Multilead ECG analysis. Comput. Biomed. Res., 1986;19: 28–46.

    Article  PubMed  CAS  Google Scholar 

  141. Macfarlane, P.W., B. Devine, S. Latif, S. McLaughlin, D.B. Shoat, and M.P. Watts, Methodology of ECG interpretation in the Glasgow program. Methods Inf. Med., 1990;29: 354–361.

    PubMed  CAS  Google Scholar 

  142. Christov, I., G. Bortolan, and I. Daskalov, Automatic detection of atrial fibrillation and flutter by wave rectification method. J. Med. Eng. Technol., 2001;25: 217–221.

    Article  PubMed  CAS  Google Scholar 

  143. Balda, R.A., G. Diller, E. Deardorff, J.C. Doue, and P. Hsieh, The HP ECG analysis program, in Trends in Computer-Processed Electrocardiograms, J.H. van Bemmel and J.L. Willems, Editors. Amsterdam: North-Holland, 1977, pp. 197–204.

    Google Scholar 

  144. Laguna, P., R. Jane, and P. Caminal, Automatic detection of wave boundaries in multilead ECG signals: validation with the CSE database. Comput. Biomed. Res., 1994;27: 45–60.

    Article  PubMed  CAS  Google Scholar 

  145. Willems, J.L. and H.V. Pipberger, Arrhythmia detection by digital computer. Comput. Biomed. Res., 1972;5: 273–278.

    Article  PubMed  CAS  Google Scholar 

  146. McManus, C.D., A re-examination of automatic P-wave recognition methods, in Optimization of Computer ECG Processing, H.K. Wolf and P.W. Macfarlane, Editors. Amsterdam: North-Holland, 1980, pp. 121–127.

    Google Scholar 

  147. Bonner, R.E. and H.D. Schwetman, Computer diagnosis of electrocardiograms. II. A computer program for EKG measurements. Comput. Biomed. Res., 1968;1: 366–386.

    Article  PubMed  CAS  Google Scholar 

  148. Hengeveld, S.J. and J.H. Bemmel, Computer detection of P-waves. Comput. Biomed. Res., 1976;9: 125–132.

    Article  PubMed  CAS  Google Scholar 

  149. Schnyders, H.C. and M. Jordan, Energy correlation technique for small P-wave detection in the presence of noise, in Computers in Cardiology 1980, K.L. Ripley and H.G. Ostrow, Editors. Los Angeles: IEEE Comput Soc, 1980, pp. 161–164.

    Google Scholar 

  150. Gritzali, F., G. Frangakis, and G. Papakonstantinou, Detection of the P and T waves in an ECG. Comput. Biomed. Res., 1989;22: 83–91.

    Article  PubMed  CAS  Google Scholar 

  151. Talmon, J.L., J.A. Kors, and J.H. van Bemmel, Algorithms for the detection of events in electrocardiograms. Comput. Methods Programs Biomed., 1986;22: 149–161.

    Article  PubMed  CAS  Google Scholar 

  152. Taha, B., S. Reddy, Q. Xue, and S. Swiryn, Automated discrimination between atrial fibrillation and atrial flutter in the resting 12-lead electrocardiogram. J. Electrocardiol., 2000;33(Suppl): 123–125.

    Article  PubMed  Google Scholar 

  153. Giraldo, B.F., P. Laguna, R. Jane, and P. Caminal, Automatic detection of atrial fibrillation and flutter using the differentiated ECG signal, in Computers in Cardiology 1995, A. Murray and R.C. Arzbaecher, Editors. Piscataway, NJ: IEEE Comput Soc, 1995, pp. 369–372.

    Chapter  Google Scholar 

  154. Bonner, R.E., L. Crevasse, M.I. Ferrer, and J.C. Greenfield, A new computer program for analysis of scalar electrocardiograms. Comput. Biomed. Res., 1972;5: 629–653.

    Article  PubMed  CAS  Google Scholar 

  155. van Bemmel, J.H. and S.J. Hengeveld, Clustering algorithm for QRS and ST-T waveform typing. Comput. Biomed. Res., 1973;6: 442–456.

    Article  PubMed  Google Scholar 

  156. Simoons, M.L., H.B. Boom, and E. Smallenburg, On-line processing of orthogonal exercise electrocardiograms. Comput. Biomed. Res., 1975;8: 105–117.

    Article  PubMed  CAS  Google Scholar 

  157. Moraes, J.C.T.B., M.O. Seixas, F.N. Vilani, and E.V. Costa, A real time QRS complex classification method using Mahalanobis distance, in Computers in Cardiology 2002, A. Murray, Editor. Piscataway, NJ: IEEE Comput Soc, 2002, pp. 201–204.

    Google Scholar 

  158. Lagerholm, M., C. Peterson, G. Braccini, L. Edenbrandt, and L. Sörnmo, Clustering ECG complexes using hermite functions and self-organizing maps. IEEE Trans. Biomed. Eng., 2000;47: 838–848.

    Article  PubMed  CAS  Google Scholar 

  159. Hu, Y.H., A patient-adaptable ECG beat classifier using a mixture of experts approach. IEEE Trans. Biomed. Eng., 1997;44: 891–900.

    Article  PubMed  CAS  Google Scholar 

  160. Wieben, O., V.X. Afonso, and W.J. Tompkins, Classification of premature ventricular complexes using filter bank features, induction of decision trees and a fuzzy rule-based system. Med. Biol. Eng. Comput., 1999;37: 560–565.

    Article  PubMed  CAS  Google Scholar 

  161. de Chazal, P., M. O’Dwyer, and R.B. Reilly, Automatic classification of heartbeats using ECG morphology and heartbeat interval features. IEEE Trans. Biomed. Eng., 2004;51: 1196–1206.

    Article  PubMed  Google Scholar 

  162. Christov, I., I. Jekova, and G. Bortolan, Premature ventricular contraction classification by the Kth nearest-neighbours rule. Physiol. Meas., 2005;26: 123–130.

    Article  PubMed  CAS  Google Scholar 

  163. Zywietz, C., D. Borovsky, G. Gotsch, and G. Joseph, Methodology of ECG interpretation in the Hannover program. Methods Inf. Med., 1990;29: 375–385.

    PubMed  CAS  Google Scholar 

  164. Rautaharju, P.M., P.J. MacInnis, J.W. Warren, H.K. Wolf, P.M. Rykers, and H.P. Calhoun, Methodology of ECG interpretation in the Dalhousie program; NOVACODE ECG classification procedures for clinical trials and population health surveys. Methods Inf. Med., 1990;29: 362–374.

    PubMed  CAS  Google Scholar 

  165. Rompelman, O. and H.H. Ros, Coherent averaging technique: a tutorial review. Part 1: Noise reduction and the equivalent filter. J. Biomed. Eng., 1986;8: 24–29.

    Article  PubMed  CAS  Google Scholar 

  166. Rompelman, O. and H.H. Ros, Coherent averaging technique: a tutorial review. Part 2: Trigger jitter, overlapping responses and non-periodic stimulation. J. Biomed. Eng., 1986;8: 30–35.

    Article  PubMed  CAS  Google Scholar 

  167. Mertens, J. and D.W. Mortara, A new algorithm for QRS averaging, in Computers in Cardiology 1984, K.L. Ripley, Editor. Long Beach: IEEE Comput Soc, 1984, pp. 367–369.

    Google Scholar 

  168. Arnaud, P., P. Rubel, D. Morlet, J. Fayn, and M.C. Forlini, Methodology of ECG interpretation in the Lyon program. Methods Inf. Med., 1990;29: 393–402.

    PubMed  CAS  Google Scholar 

  169. Goetowski, C.R., The Telemed system, in Trends in Computer-Processed Electrocardiograms, J.H. van Bemmel and J.L. Willems, Editors. Amsterdam: North-Holland, 1977, pp. 207–210.

    Google Scholar 

  170. Degani, R. and G. Bortolan, Methodology of ECG interpretation in the Padova program. Methods Inf. Med., 1990;29: 386–392.

    PubMed  CAS  Google Scholar 

  171. Willems, J.L., C. Zywietz, P. Arnaud, J.H. van Bemmel, R. Degani, and P.W. Macfarlane, Influence of noise on wave boundary recognition by ECG measurement programs. Recommendations for preprocessing. Comput. Biomed. Res., 1987;20: 543–562.

    Google Scholar 

  172. Zywietz, C., J.L. Willems, P. Arnaud, J.H. van Bemmel, R. Degani, P.W. Macfarlane, et al., Stability of computer ECG amplitude measurements in the presence of noise. Comput. Biomed. Res., 1990;23: 10–31.

    Article  PubMed  CAS  Google Scholar 

  173. Day, C.P., J.M. McComb, and R.W. Campbell, QT dispersion: an indication of arrhythmia risk in patients with long QT intervals. Br. Heart J., 1990;63: 342–344.

    Article  PubMed  CAS  Google Scholar 

  174. Kors, J.A., G. van Herpen, and J.H. van Bemmel, QT dispersion as an attribute of T-loop morphology. Circulation, 1999;99: 1458–1463.

    Article  PubMed  CAS  Google Scholar 

  175. Rautaharju, P.M., QT and dispersion of ventricular repolarization: the greatest fallacy in electrocardiography in the 1990s. Circulation, 1999;99: 2477–2478.

    PubMed  CAS  Google Scholar 

  176. Malik, M., B. Acar, Y. Gang, Y.G. Yap, K. Hnatkova, and A.J. Camm, QT dispersion does not represent electrocardiographic interlead heterogeneity of ventricular repolarization. J. Cardiovasc. Electrophysiol., 2000;11: 835–843.

    Article  PubMed  CAS  Google Scholar 

  177. van Herpen, G., H.J. Ritsema van Eck, and J.A. Kors, The evidence against QT dispersion. Int. J. Bioelectromagn., 2003;5: 231–233.

    Google Scholar 

  178. Ritsema van Eck, H.J., J.A. Kors, and G. van Herpen, The U wave in the electrocardiogram: a solution for a 100-year-old riddle. Cardiovasc. Res., 2005;67: 256–262.

    Article  PubMed  CAS  Google Scholar 

  179. Nygards, M.E. and L. Sörnmo, Delineation of the QRS complex using the envelope of the e.c.g. Med. Biol. Eng. Comput., 1983;21: 538–547.

    Article  PubMed  CAS  Google Scholar 

  180. van Bemmel, J.H., C. Zywietz, and J.A. Kors, Signal analysis for ECG interpretation. Methods Inf. Med., 1990;29: 317–329.

    PubMed  Google Scholar 

  181. McLaughlin, N.B., R.W. Campbell, and A. Murray, Comparison of automatic QT measurement techniques in the normal 12 lead electrocardiogram. Br. Heart J., 1995;74: 84–89.

    Article  PubMed  CAS  Google Scholar 

  182. McLaughlin, N.B., R.W. Campbell, and A. Murray, Accuracy of four automatic QT measurement techniques in cardiac patients and healthy subjects. Heart, 1996;76: 422–426.

    Article  PubMed  CAS  Google Scholar 

  183. Vila, J.A., Y. Gang, J.M. Rodriguez Presedo, M. Fernandez-Delgado, S. Barro, and M. Malik, A new approach for TU complex characterization. IEEE Trans. Biomed. Eng., 2000;47: 764–772.

    Article  PubMed  CAS  Google Scholar 

  184. Rubel, P. and B. Ayad, The true boundary recognition power of multidimensional detection functions. An optimal comparison, in Computer ECG Analysis: Towards Standardization, J.L. Willems, J.H. van Bemmel, and C. Zywietz, Editors. Amsterdam: North-Holland, 1986, pp. 97–103.

    Google Scholar 

  185. van Bemmel, J.H., J.L. Talmon, J.S. Duisterhout, and S.J. Hengeveld, Template waveform recognition applied to ECG-VCG analysis. Comput. Biomed. Res., 1973;6: 430–441.

    Article  PubMed  Google Scholar 

  186. Zhang, Q., A. Illanes Manriquez, C. Medigue, Y. Papelier, and M. Sorine, Robust and efficient location of T-wave ends in electrocardiogram, in Computers in Cardiology, A. Murray, Editor. Piscataway, NJ: IEEE Comput Soc, 2005, pp. 711–714.

    Google Scholar 

  187. Sörnmo, L., A model-based approach to QRS delineation. Comput. Biomed. Res., 1987;20: 526–542.

    Article  PubMed  Google Scholar 

  188. Morlet, D., P. Rubel, P. Arnaud, and J.L. Willems, An improved method to evaluate the precision of computer ECG measurement programs. Int. J. Biomed. Comput., 1988;22: 199–216.

    Article  PubMed  CAS  Google Scholar 

  189. Kors, J.A., G. van Herpen, A.C. Sittig, and J.H. van Bemmel, Reconstruction of the Frank vectorcardiogram from standard electrocardiographic leads: diagnostic comparison of different methods. Eur. Heart J., 1990;11: 1083–1092.

    PubMed  CAS  Google Scholar 

  190. Young, T.Y. and W.H. Huggins, Intrinsic component theory of electrocardiograms. IEEE Trans. Biomed. Eng., 1963;9: 214–221.

    Google Scholar 

  191. Horan, L.G., N.C. Flowers, and D.A. Brody, Principal factor waveforms of the thoracic QRS complex. Circ. Res., 1964;15: 131–145.

    Article  PubMed  CAS  Google Scholar 

  192. Willems, J.L., Introduction to multivariate and conventional computer ECG analysis: pro’s and contra’s, in Trends in Computer-Processed Electrocardiograms, J.H. van Bemmel and J.L. Willems, Editors. Amsterdam: North-Holland, 1977, pp. 213–220.

    Google Scholar 

  193. Smets, P., New quantified approach for diagnostic classification, in Optimization of Computer ECG Processing, H.K. Wolf and P.W. Macfarlane, Editors. Amsterdam: North-Holland, 1980, pp. 229–237.

    Google Scholar 

  194. Degani, R. and G. Bortolan, Combining measurement precision and fuzzy diagnostic criteria, in Computer ECG Analysis: Towards Standardization, J.L. Willems, J.H. van Bemmel, and C. Zywietz, Editors. Amsterdam: North-Holland, 1986, pp. 177–182.

    Google Scholar 

  195. Doue, J.C., The role of artificial intelligence in standardizing ECG criteria, in Computer ECG Analysis: Towards Standardization, J.L. Willems, J.H. van Bemmel, and C. Zywietz, Editors. Amsterdam: North-Holland, 1986, pp. 53–57.

    Google Scholar 

  196. Matthes, T., G. Götsch, and C. Zywietz, Interactive analysis of statistical ECG diagnosis on an intelligent electrocardiograph. An expert system approach, in Computer ECG Analysis: Towards Standardization, J.L. Willems, J.H. van Bemmel, and C. Zywietz, Editors. Amsterdam: North-Holland, 1986, pp. 215–220.

    Google Scholar 

  197. Edenbrandt, L., B. Devine, and P.W. Macfarlane, Neural networks for classification of ECG ST-T segments. J. Electrocardiol., 1992;25: 167–173.

    Article  PubMed  CAS  Google Scholar 

  198. Yang, T.F., B. Devine, and P.W. Macfarlane, Use of artificial neural networks within deterministic logic for the computer ECG diagnosis of inferior myocardial infarction. J. Electrocardiol., 1994;27(Suppl): 188–193.

    Article  PubMed  Google Scholar 

  199. Kennedy, R.L., A.M. Burton, and R.F. Harrison, Neural networks and early diagnosis of myocardial infarction. Lancet, 1996;347: 407.

    Google Scholar 

  200. Hedén, B., H. Ohlin, R. Rittner, and L. Edenbrandt, Acute myocardial infarction detected in the 12-lead ECG by artificial neural networks. Circulation, 1997;96: 1798–1802.

    Article  PubMed  Google Scholar 

  201. Olsson, S.E., M. Ohlsson, H. Ohlin, and L. Edenbrandt, Neural networks—a diagnostic tool in acute myocardial infarction with concomitant left bundle branch block. Clin. Physiol. Funct. Imaging, 2002;22: 295–299.

    Article  PubMed  Google Scholar 

  202. Segall, H.N., The electrocardiogram and its interpretation: a study of reports by 20 physicians on a set of 100 electrocardiograms. Can. Med. Assoc. J., 1960;82: 847–850.

    Google Scholar 

  203. Simonson, E., N. Tuna, and N. Okamoto, Diagnostic accuracy of the vectorcardiogram and electrocardiogram. A cooperative study. Am. J. Cardiol., 1966;17: 829–878.

    Article  Google Scholar 

  204. Willems, J.L., C. Abreu-Lima, P. Arnaud, J.H. van Bemmel, C. Brohet, R. Degani, et al., Effect of combining electrocardiographic interpretation results on diagnostic accuracy. Eur. Heart J., 1988;9: 1348–1355.

    PubMed  CAS  Google Scholar 

  205. Balda, R.A., A.G. Vallance, J.M. Luszcz, F.J. Stahlin, and G. Diller, ECL—a medically oriented ECG criteria language and other clinical research tools, in Computers in Cardiology 1977, H.G. Ostrow and K.L. Ripley, Editors. New York: IEEE Comput Soc, 1977, pp. 481–495.

    Google Scholar 

  206. Bruce, R.A. and S.R. Yarnall, Reliability and normal variations of computer analysis of Frank electrocardiogram by Smith-Hyde program (1968 version). Am. J. Cardiol., 1972;29: 389–396.

    Article  PubMed  CAS  Google Scholar 

  207. Willems, J.L., C. Abreu-Lima, P. Arnaud, J.H. van Bemmel, C. Brohet, R. Degani, et al., The diagnostic performance of computer programs for the interpretation of electrocardiograms. N. Engl. J. Med., 1991;325: 1767–1773.

    Article  PubMed  CAS  Google Scholar 

  208. Breiman, L., J.H. Friedman, R.A. Olshen, and C.J. Stone, Classification and Regression Trees. Belmont, CA: Wadsworth, 1984.

    Google Scholar 

  209. Kors, J.A. and A.L. Hoffmann, Induction of decision rules that fulfill user-specified performance requirements. Pattern Recognit. Lett., 1997;18: 1187–1195.

    Article  Google Scholar 

  210. Pipberger, H.V., R.A. Dunn, and J. Cornfield, First and second generation computer programs for diagnostic ECG and VCG classification, in XIIth International Colloquium Vectorcardiographicum, P. Rijlant, Editor. Brussels: Presses Académiques Européennes, 1972, pp. 431–439.

    Google Scholar 

  211. Willems, J.L. and J. Pardaens, Reproducibility of diagnostic results by a multivariate computer ECG analysis program (AVA 3.5). Eur. J. Cardiol., 1977;6: 229–243.

    PubMed  CAS  Google Scholar 

  212. Dunn, R.A., R. Babuska, J.M. Wojick, and H.V. Pipberger, Variation in probability levels in electrocardiographic diagnosis. Comput. Biomed. Res., 1978;11: 41–49.

    Article  PubMed  CAS  Google Scholar 

  213. Cady, L.D., M.A. Woodbury, L.J. Tick, and M.M.A. Gertler, Method for electrocardiogram wave pattern estimation. Example: left ventricular hypertrophy. Circ. Res., 1961;9: 1078– 1082.

    Google Scholar 

  214. Kimura, E., Y. Mibukura, and A. Miura, Statistical diagnosis of electrocardiogram by theorem of Bayes. A preliminary report. Jpn. Heart J., 1963;4: 469–488.

    Article  Google Scholar 

  215. Young, T.Y. and W.H. Huggins, Computer analysis of electrocardiograms using a linear regression technique. IEEE Trans. Biomed. Eng., 1964;11: 60–67.

    Article  PubMed  CAS  Google Scholar 

  216. Stark, L., J.F. Dickson, G.H. Whipple, and H. Horibe, Remote real-time diagnosis of clinical electrocardiograms by a digital computer system. Ann. N.Y. Acad. Sci., 1965;126: 851–872.

    Article  PubMed  CAS  Google Scholar 

  217. Specht, D.F., Vectorcardiographic diagnosis using the polynomial discriminant method of pattern recognition. IEEE Trans. Biomed. Eng., 1967;14: 90–95.

    Article  PubMed  CAS  Google Scholar 

  218. Yasui, S., M. Yokoi, Y. Watanabe, K. Nishijima, and S. Azuma, Computer diagnosis of electrocardiograms by means of the joint probability. Jpn. Circ. J., 1968;32: 517–523.

    Article  PubMed  CAS  Google Scholar 

  219. Goldman, M.J. and H.V. Pipberger, Analysis of the orthogonal electrocardiogram and vectorcardiogram in ventricular conduction defects with and without myocardial infarction. Circulation, 1969;39: 243–250.

    Article  PubMed  CAS  Google Scholar 

  220. Kerr, A., A. Adicoff, J.D. Klingeman, and H.V. Pipberger, Computer analysis of the orthogonal electrocardiogram in pulmonary emphysema. Am. J. Cardiol., 1970;25: 34–45.

    Article  PubMed  Google Scholar 

  221. Eddleman, E.E. and H.V. Pipberger, Computer analysis of the orthogonal electrocardiogram and vectorcardiogram in 1,002 patients with myocardial infarction. Am. Heart J., 1971;81: 608–621.

    Article  PubMed  Google Scholar 

  222. Pipberger, H.V., ECG computer analysis: past, present and future, in Computer ECG Analysis: Towards Standardization, J.L. Willems, J.H. van Bemmel, and C. Zywietz, Editors. Amsterdam: North-Holland, 1986, pp. 3–10.

    Google Scholar 

  223. Brohet, C.R., A. Robert, C. Derwael, R. Fesler, M. Stijns, A. Vliers, et al., Computer interpretation of pediatric orthogonal electrocardiograms: statistical and deterministic classification methods. Circulation, 1984;70: 255–262.

    Article  PubMed  CAS  Google Scholar 

  224. Willems, J.L., E. Lesaffre, J. Pardaens, and D. de Schreye, Multivariate logistic classification of the standard 12- and 3-lead ECG, in Computer ECG Analysis: Towards Standardization, J.L. Willems, J.H. van Bemmel, and C. Zywietz, Editors. Amsterdam: North-Holland, 1986, pp. 203–210.

    Google Scholar 

  225. Rios, J., F. Sandquist, D. Ramseth, R. Stratbucker, E. Drazen, and J. Hanmer, The quest for optimal electrocardiography. Tast force V: cost effectiveness of the electrocardiogram. Am. J. Cardiol., 1978;41: 175–183.

    Article  PubMed  CAS  Google Scholar 

  226. Okajima, M., Current status and future optimization of computerized electrocardiography in Japan, in Optimization of Computer ECG Processing, H.K. Wolf and P.W. Macfarlane, Editors. Amsterdam: North-Holland, 1980, pp. 293–307.

    Google Scholar 

  227. Moorman, J.R., M.A. Hlatky, D.M. Eddy, and G.S. Wagner, The yield of the routine admission electrocardiogram. A study in a general medical service. Ann. Intern. Med., 1985;103: 590–595.

    PubMed  CAS  Google Scholar 

  228. Salerno, S.M., P.C. Alguire, and H.S. Waxman, Competency in interpretation of 12-lead electrocardiograms: a summary and appraisal of published evidence. Ann. Intern. Med., 2003;138: 751–760.

    PubMed  Google Scholar 

  229. Eisenstein, E.L., Conducting an economic analysis to assess the electrocardiogram’s value. J. Electrocardiol., 2006;39: 241–247.

    Article  PubMed  Google Scholar 

  230. Willems, J.L., C. Abreu-Lima, P. Arnaud, C.R. Brohet, B. Denis, J. Gehring, et al., Evaluation of ECG interpretation results obtained by computer and cardiologists. Methods Inf. Med., 1990;29: 308–316.

    PubMed  CAS  Google Scholar 

  231. Farb, A., R.B. Devereux, and P. Kligfield, Day-to-day variability of voltage measurements used in electrocardiographic criteria for left ventricular hypertrophy. J. Am. Coll. Cardiol., 1990;15: 618–623.

    Article  PubMed  CAS  Google Scholar 

  232. van den Hoogen, J.P., W.H. Mol, A. Kowsoleea, J.W. van Ree, T. Thien, and C. van Weel, Reproducibility of electrocardiographic criteria for left ventricular hypertrophy in hypertensive patients in general practice. Eur. Heart J., 1992;13: 1606–1610.

    Google Scholar 

  233. de Bruyne, M.C., J.A. Kors, S. Visentin, G. van Herpen, A.W. Hoes, D.E. Grobbee, et al., Reproducibility of computerized ECG measurements and coding in a nonhospitalized elderly population. J. Electrocardiol., 1998;31: 189–195.

    Article  PubMed  Google Scholar 

  234. Bailey, J.J., M. Horton, S.B. Itscoitz, A method for evaluating computer programs for electrocardiographic interpretation. 3. Reproducibility testing and the sources of program errors. Circulation, 1974;50: 88–93.

    Article  PubMed  CAS  Google Scholar 

  235. Bailey, J.J., M. Horton, and S.B. Itscoitz, The importance of reproducibility testing of computer programs for electrocardiographic interpretation: application to the automatic vectorcardiographic analysis program (AVA 3.4). Comput. Biomed. Res., 1976;9: 307–316.

    Article  PubMed  CAS  Google Scholar 

  236. Spodick, D.H. and R.L. Bishop, Computer treason: intraobserver variability of an electrocardiographic computer system. Am. J. Cardiol., 1997;80: 102–103.

    Article  PubMed  CAS  Google Scholar 

  237. Michaelis, J., S. Wellek, and J.L. Willems, Reference standards for software evaluation. Methods Inf. Med., 1990;29: 289–297.

    PubMed  CAS  Google Scholar 

  238. Jakobsson, A., P. Ohlin, and O. Pahlm, Does a computer-based ECG-recorder interpret electrocardiograms more efficiently than physicians? Clin. Physiol., 1985;5: 417–423.

    Article  PubMed  CAS  Google Scholar 

  239. Bernard, P., B.R. Chaitman, J.M. Scholl, P.G. Val, and M. Chabot, Comparative diagnostic performance of the Telemed computer ECG program. J. Electrocardiol., 1983;16: 97–103.

    Article  PubMed  CAS  Google Scholar 

  240. Willems, J.L., Is human verification of computerized ECGs mandatory? Adv. Cardiol., 1978;21: 193–194.

    Google Scholar 

  241. Chou, T.C., When is the vectorcardiogram superior to the scalar electrocardiogram? J. Am. Coll. Cardiol., 1986;8: 791–799.

    Article  PubMed  CAS  Google Scholar 

  242. Kors, J.A., G. van Herpen, J.L. Willems, and J.H. van Bemmel, Improvement of automated electrocardiographic diagnosis by combination of computer interpretations of the electrocardiogram and vectorcardiogram. Am. J. Cardiol., 1992;70: 96–99.

    Article  PubMed  CAS  Google Scholar 

  243. Kors, J.A., G. van Herpen, and J.H. van Bemmel, Variability in ECG computer interpretation. Analysis of individual complexes vs analysis of a representative complex. J. Electrocardiol., 1992;25: 263–271.

    Article  PubMed  CAS  Google Scholar 

  244. Andresen, A., J. Dobkin, C. Maynard, R. Myers, G.S. Wagner, R.A. Warner, et al., Validation of advanced ECG diagnostic software for the detection of prior myocardial infarction by using nuclear cardiac imaging. J. Electrocardiol., 2001;34(Suppl): 243–248.

    Article  PubMed  Google Scholar 

  245. Andresen, A., M.D. Gasperina, R. Myers, G.S. Wagner, R.A. Warner, and R.H. Selvester, An improved automated ECG algorithm for detecting acute and prior myocardial infarction. J. Electrocardiol., 2002;35(Suppl): 105–110.

    Article  PubMed  Google Scholar 

  246. Wagner, G.S., C. Maynard, A. Andresen, E. Anderson, R. Myers, R.A. Warner, et al., Evaluation of advanced electrocardiographic diagnostic software for detection of prior myocardial infarction. Am. J. Cardiol., 2002;89: 75–79.

    Article  PubMed  Google Scholar 

  247. Milliken, J.A., H. Pipberger, H.V. Pipberger, M.A. Araoye, R. Ari, G.W. Burggraf, et al., The impact of an ECG computer analysis program on the cardiologist’s interpretation. A cooperative study. J. Electrocardiol., 1983;16: 141–149.

    Google Scholar 

  248. Hillson, S.D., D.P. Connelly, and Y. Liu, The effects of computer-assisted electrocardiographic interpretation on physicians’ diagnostic decisions. Med. Decis. Making, 1995;15: 107–112.

    Article  PubMed  CAS  Google Scholar 

  249. Brailer, D.J., E. Kroch, and M.V. Pauly, The impact of computer-assisted test interpretation on physician decision making: the case of electrocardiograms. Med. Decis. Making, 1997;17: 80–86.

    Article  PubMed  CAS  Google Scholar 

  250. Goodacre, S., A. Webster, and F. Morris, Do computer generated ECG reports improve interpretation by accident and emergency senior house officers? Postgrad. Med. J., 2001;77: 455–457.

    Article  PubMed  CAS  Google Scholar 

  251. Tsai, T.L., D.B. Fridsma, and G. Gatti, Computer decision support as a source of interpretation error: the case of electrocardiograms. J. Am. Med. Inform. Assoc., 2003;10: 478–483.

    Article  PubMed  Google Scholar 

  252. Laks, M.M. and R.H. Selvester, Computerized electrocardiography – an adjunct to the physician. N. Engl. J. Med., 1991;325: 1803–1804.

    Article  PubMed  CAS  Google Scholar 

  253. Plokker, H.W.M., Cardiac Rhythm Diagnosis by Digital Computer, dissertation. Amsterdam: Free University, 1978.

    Google Scholar 

  254. Reddy, S., B. Young, Q. Xue, B. Taha, D. Brodnick, and J. Steinberg, Review of methods to predict and detect atrial fibrillation in post-cardiac surgery patients. J. Electrocardiol., 1999;32(Suppl): 23–28.

    Article  PubMed  Google Scholar 

  255. Poon, K., P.M. Okin, and P. Kligfield, Diagnostic performance of a computer-based ECG rhythm algorithm. J. Electrocardiol., 2005;38: 235–238.

    Article  PubMed  Google Scholar 

  256. Bonner, R.E. and H.D. Schwetman, Computer diagnosis of electrocardiograms. 3. A computer program for arrhythmia diagnosis. Comput. Biomed. Res., 1968;1: 387–407.

    Google Scholar 

  257. Bonner, R.E., IBM rhythm analysis program, in Computer Application on ECG and VCG Analysis, C. Zywietz and B. Schneider, Editors. Amsterdam: North-Holland, 1973, pp. 375–397.

    Google Scholar 

  258. Wartak, J., J.A. Milliken, and J. Karchmar, Computer program for diagnostic evaluation of electrocardiograms. Comput. Biomed. Res., 1971;4: 225–238.

    Article  PubMed  CAS  Google Scholar 

  259. Brohet, C., C. Derwael, R. Fesler, and L.A. Brasseur, Arrhythmia analysis by the Louvain VCG program, in Computers in Cardiology, K.L. Ripley, Editor. Los Angeles: IEEE Comput Soc, 1982, pp. 47–51.

    Google Scholar 

  260. Shirataka, M., H. Miyahara, N. Ikeda, A. Domae, and T. Sato, Evaluation of five computer programs in the diagnosis of second-degree AV block. J. Electrocardiol., 1992;25: 185–195.

    Article  PubMed  CAS  Google Scholar 

  261. Thomson, A., S. Mitchell, and P.J. Harris, Computerized electrocardiographic interpretation: an analysis of clinical utility in 5110 electrocardiograms. Med. J. Aust., 1989;151: 428–430.

    PubMed  CAS  Google Scholar 

  262. Reddy, B.R., B. Taha, S. Swiryn, R. Silberman, and R. Childers, Prospective evaluation of a microprocessor-assisted cardiac rhythm algorithm: results from one clinical center. J. Electrocardiol., 1998;30(Suppl): 28–33.

    Article  PubMed  Google Scholar 

  263. Farrell, R.M., J.Q. Xue, and B.J. Young, Enhanced rhythm analysis for resting ECG using spectral and time-domain techniques, in Computers in Cardiology, A. Murray, Editor. Piscataway, NJ: IEEE Comput Soc, 2003, pp. 733–736.

    Google Scholar 

  264. Guglin, M.E. and D. Thatai, Common errors in computer electrocardiogram interpretation. Int. J. Cardiol., 2006;106: 232–237.

    Article  PubMed  Google Scholar 

  265. Pryor, T.A., A.E. Lindsay, and R.W. England, Computer analysis of serial electrocardiograms. Comput. Biomed. Res., 1972;5: 709–714.

    Article  PubMed  CAS  Google Scholar 

  266. Macfarlane, P.W., H.T. Cawood, and T.D. Lawrie, A basis for computer interpretation of interpretation of serial electrocardiograms. Comput. Biomed. Res., 1975;8: 189–200.

    Article  PubMed  CAS  Google Scholar 

  267. Bonner, R.E., L. Crevasse, M.I. Ferrer, and J.C. Greenfield, A new computer program for comparative analysis of serial scalar electrocardiograms: description and performance of the 1976 IBM program. Comput. Biomed. Res., 1978;11: 103–118.

    Article  PubMed  CAS  Google Scholar 

  268. Schnyders, H.C. and G.A. Kien, Computer-assisted serial comparison of ECGs: the Telemed version, in Computer Application in Medical Care, R.A. Dunn, Editor. New York: IEEE Comput Soc, 1979, pp. 652–659.

    Google Scholar 

  269. Rubel, P., J. Fayn, J.L. Willems, and C. Zywietz, New trends in serial ECG analysis. J. Electrocardiol., 1993;26(Suppl): 122–128.

    PubMed  Google Scholar 

  270. Rubel, P., J. Fayn, G. Nollo, D. Assanelli, B. Li, L. Restier, et al, Toward personal eHealth in cardiology. Results from the EPI-MEDICS telemedicine project. J. Electrocardiol., 2005;38(Suppl): 100–106.

    Google Scholar 

  271. Willems, J.L., P.F. Poblete, and H.V. Pipberger, Day-to-day variation of the normal orthogonal electrocardiogram and vectorcardiogram. Circulation, 1972;45: 1057–1064.

    Article  PubMed  CAS  Google Scholar 

  272. de Bruyne, M.C., J.A. Kors, S. Visentin, G. van Herpen, A.W. Hoes, D.E. Grobbee, et al., Reproducibility of computerized ECG measurements and coding in a nonhospitalized elderly population. J. Electrocardiol., 1998;31: 189–195.

    Article  PubMed  Google Scholar 

  273. Schijvenaars, B.J., Intra-individual Variability of the Electrocardiogram, dissertation. Rotterdam: Erasmus University, 2000.

    Google Scholar 

  274. Pipberger, H.V., R.A. Dunn, and H.A. Pipberger, Automated comparison of serial electrocardiograms. Adv. Cardiol., 1976;16: 157–165.

    PubMed  CAS  Google Scholar 

  275. Rubel, P., N. Saccal, J.L. Sourrouille, and M.C. Forlini, Multidimensional techniques for the optimal display of trends in sequential vectorcardiograms, in Medinfo 1980, D.A.B. Lindberg and S. Kaihara, Editors. Amsterdam: North-Holland, 1980, p. 274.

    Google Scholar 

  276. Zywietz, C., B. Widiger, and R. Fischer, A system for comprehensive comparison of serial ECG beats and serial ECG recordings, in Computers in Cardiology, A. Murray, Editor. Piscataway, NJ: IEEE Comput Soc, 2003, pp. 689–692.

    Google Scholar 

  277. Hedstrom, K. and P.W. Macfarlane, Development of a new approach to serial analysis. The manufacturer’s viewpoint. J. Electrocardiol., 1996;29(Suppl): 35–40.

    Article  PubMed  Google Scholar 

  278. McLaughlin, S.C., T.C. Aitchison, and P.W. Macfarlane, Methods for improving the repeatability of automated ECG analysis. Methods Inf. Med., 1995;34: 272–282.

    PubMed  CAS  Google Scholar 

  279. McLaughlin, S.C., P. Chishti, T.C. Aitchison, and P.W. Macfarlane, Techniques for improving overall consistency of serial ECG analysis. J. Electrocardiol., 1996;29(Suppl): 41–45.

    Article  PubMed  Google Scholar 

  280. Fayn, J. and P. Rubel, CAVIAR: a serial ECG processing system for the comparative analysis of VCGs and their interpretation with auto-reference to the patient. J. Electrocardiol., 1988;21(Suppl): S173–S176.

    Article  PubMed  Google Scholar 

  281. Sunemark, M., L. Edenbrandt, H. Holst, and L. Sörnmo, Serial VCG/ECG analysis using neural networks. Comput. Biomed. Res., 1998;31: 59–69.

    Article  PubMed  CAS  Google Scholar 

  282. Bonner, R.E., L. Crevasse, M.I. Ferrer, and J.C. Greenfield, The influence of editing on the performance of a computer program for serial comparison of electrocardiograms. J. Electrocardiol., 1983;16: 181–189.

    Article  PubMed  CAS  Google Scholar 

  283. van Haelst, A.C., D.K. Donker, F.C. Visser, C.C. de Cock, A. Hasman, and J.L. Talmon, A computer program for the analysis of serial electrocardiograms from patients who suffered a myocardial infarction. Int. J. Biomed. Comput., 1985;17: 273–284.

    Article  PubMed  Google Scholar 

  284. Ohlsson, M., H. Ohlin, S.M. Wallerstedt, and L. Edenbrandt, Usefulness of serial electrocardiograms for diagnosis of acute myocardial infarction. Am. J. Cardiol., 2001;88: 478– 481.

    Article  PubMed  CAS  Google Scholar 

  285. Schwartz, P.J., A. Garson, T. Paul, M. Stramba-Badiale, V.L. Vetter, and C. Wren, Guidelines for the interpretation of the neonatal electrocardiogram. A task force of the European Society of Cardiology. Eur. Heart J., 2002;23: 1329–1344.

    Google Scholar 

  286. Dickinson, D.F., The normal ECG in childhood and adolescence. Heart, 2005;91: 1626–1630.

    Article  PubMed  Google Scholar 

  287. Davignon, A., P.M. Rautaharju, E. Boisselle, F. Soumis, M. Megelas, and A. Choguette, Normal ECG standards for infants and children. Pediatr. Cardiol., 1979/80;1: 123–131.

    Article  Google Scholar 

  288. Brohet, C.R., C. Hoeven, A. Robert, C. Derwael, R. Fesler, and L.A. Brasseur, The normal pediatric Frank orthogonal electrocardiogram: variations according to age and sex. J. Electrocardiol., 1986;19: 1–13.

    Article  PubMed  CAS  Google Scholar 

  289. Perry, L.W., H.V. Pipberger, H.A. Pipberger, C.D. McManus, and L.P. Scott, Scalar, planar, and spatial measurements of the Frank vectorcardiogram in normal infants and children. Am. Heart J., 1986;111: 721–730.

    Article  PubMed  CAS  Google Scholar 

  290. Macfarlane, P.W., E.N. Coleman, E.O. Pomphrey, S. McLaughlin, A. Houston, and T. Aitchison, Normal limits of the high-fidelity pediatric ECG. Preliminary observations. J. Electrocardiol., 1989;22(Suppl): 162–168.

    Article  PubMed  Google Scholar 

  291. Macfarlane, P.W., S.C. McLaughlin, B. Devine, and T.F. Yang, Effects of age, sex, and race on ECG interval measurements. J. Electrocardiol., 1994;27(Suppl): 14–19.

    Article  PubMed  Google Scholar 

  292. Rijnbeek, P.R., M. Witsenburg, E. Schrama, J. Hess, and J.A. Kors, New normal limits for the paediatric electrocardiogram. Eur. Heart J., 2001;22: 702–711.

    Article  PubMed  CAS  Google Scholar 

  293. Horton, L.A., S. Mosee, and J. Brenner, Use of the electrocardiogram in a pediatric emergency department. Arch. Pediatr. Adolesc. Med., 1994;148: 184–188.

    Article  PubMed  CAS  Google Scholar 

  294. Hamilton, R.M., K. McLeod, A.B. Houston, and P.W. Macfarlane, Inter- and intraobserver variability in LVH and RVH reporting in pediatric ECGs. Ann. Noninvasive Electrocardiol., 2005;10: 330–333.

    Article  PubMed  CAS  Google Scholar 

  295. Guller, B., P.C. O’Brien, R.E. Smith, W.H. Weidman, and J.W. DuShane, Computer interpretation of Frank vectorcardiograms in normal infants: longitudinal and cross-sectional observations from birth to 2 years of age. J. Electrocardiol., 1975;8: 201–208.

    Article  PubMed  CAS  Google Scholar 

  296. Guller, B., F.Y. Lau, R.A. Dunn, H.A. Pipberger, and H.V. Pipberger, Computer analysis of changes in Frank vectorcardiograms of 666 normal infants in the first 72 hours of life. J. Electrocardiol., 1977;10: 19–26.

    Article  PubMed  CAS  Google Scholar 

  297. Francis, D.B., B.L. Miller, and D.W. Benson, A new computer program for the analysis of pediatric scalar electrocardiograms. Comput. Biomed. Res., 1981;14: 63–77.

    Article  PubMed  CAS  Google Scholar 

  298. Laks, M.M., A computer program for interpretation of infant and children electrocardiograms, in Computer ECG Analysis: Towards Standardization, J.L. Willems, J.H. van Bemmel, and C. Zywietz, Editors. Amsterdam: North-Holland, 1986, pp. 59–65.

    Google Scholar 

  299. Macfarlane, P.W., E.N. Coleman, B. Devine, A. Houston, S. McLaughlin, T.C. Aitchison, et al., A new 12-lead pediatric ECG interpretation program. J. Electrocardiol., 1990;23(Suppl): 76–81.

    Article  PubMed  Google Scholar 

  300. Rijnbeek, P.R., M. Witsenburg, A. Szatmari, J. Hess, and J.A. Kors, PEDMEANS: a computer program for the interpretation of pediatric electrocardiograms. J. Electrocardiol., 2001;34(Suppl): 85–91.

    Article  PubMed  Google Scholar 

  301. Zhou, S.H., J. Liebman, A.M. Dubin, P.C. Gillette, R.E. Gregg, E.D. Helfenbein, et al., Using 12-lead ECG and synthesized VCG in detection of right ventricular hypertrophy with terminal right conduction delay versus partial right bundle branch block in the pediatric population. J. Electrocardiol., 2001;34(Suppl): 249–257.

    Article  PubMed  Google Scholar 

  302. Guller, B., T. Jones, J. McCloskey, and S.P. Herndon, The Hewlett-Packard pediatric ECG computer program (HP-P3) and independent clinical information. J. Electrocardiol., 1990;23(Suppl): 204.

    Google Scholar 

  303. Hamilton, R.M., A.B. Houston, K. McLeod, and P.W. Macfarlane, Evaluation of pediatric electrocardiogram diagnosis of ventricular hypertrophy by computer program compared with cardiologists. Pediatr. Cardiol., 2005;26: 373–378.

    Article  PubMed  CAS  Google Scholar 

  304. Snyder, C.S., A.L. Fenrich, R.A. Friedman, C. Macias, K. O’Reilly, and N.J. Kertesz, The emergency department versus the computer: which is the better electrocardiographer? Pediatr. Cardiol., 2003;24: 364–368.

    Article  PubMed  CAS  Google Scholar 

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Kors, J.A., van Herpen, G. (2010). Computer Analysis of the Electrocardiogram. In: Macfarlane, P.W., van Oosterom, A., Pahlm, O., Kligfield, P., Janse, M., Camm, J. (eds) Comprehensive Electrocardiology. Springer, London. https://doi.org/10.1007/978-1-84882-046-3_37

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