The Application of Neural Networks in the Classification of the Electrocardiogram

The introduction of computers to assist with classification of the Electrocardiogram (ECG) is considered to be one of the earliest instances of computers in medicine. Over the past 4 decades, since its inception, research techniques in the given field have proliferated. Approaches adopted have included the use of rule based approaches such as Decision Trees, Fuzzy Logic and Expert Systems, to the use of Multivariate Statistical Analysis. The past decade has seen the approach of Neural Networks (NNs) being not only employed in the field, but a very popular and successful approach in comparison with the aforementioned techniques.

[1]  Chee Peng Lim,et al.  Application of autonomous neural network systems to medical pattern classification tasks , 1997, Artif. Intell. Medicine.

[2]  David G. Bounds,et al.  A comparison of neural network and other pattern recognition approaches to the diagnosis of low back disorders , 1990, Neural Networks.

[3]  Theodosios Pavlidis,et al.  Waveform Segmentation Through Functional Approximation , 1973, IEEE Transactions on Computers.

[4]  N D Black,et al.  Feature and classifier fusion for 12-lead ECG classification , 2000, Medical informatics and the Internet in medicine.

[5]  K. J. Siddiqui,et al.  Best feature selection using successive elemnation of poor performers , 1993, Proceedings of the 15th Annual International Conference of the IEEE Engineering in Medicine and Biology Societ.

[6]  Georg Dorffner,et al.  On using feedforward neural networks for clinical diagnostic tasks , 1994, Artif. Intell. Medicine.

[7]  O Pahlm,et al.  Neural networks for analysis of ECG complexes. , 1993, Journal of electrocardiology.

[8]  Stamatios V. Kartalopoulos,et al.  Understanding neural networks and fuzzy logic - basic concepts and applications , 1997 .

[9]  P W Macfarlane,et al.  Deterministic logic versus software-based artificial neural networks in the diagnosis of atrial fibrillation. , 1993, Journal of electrocardiology.

[10]  Paul D. White,et al.  THE STANDARDIZATION OF ELECTROCARDIOGRAPHIC NOMENCLATURE: REPORT OF COMMITTEE OF THE AMERICAN HEART ASSOCIATION , 1943 .

[11]  J A Kors,et al.  Classification Methods for Computerized Interpretation of the Electrocardiogram , 1990, Methods of Information in Medicine.

[12]  W. Baxt.  Use of an artificial neural network for the diagnosis of myocardial infarction. , 1991, Annals of internal medicine.

[13]  C Zywietz,et al.  Common Standards for Quantitative Electrocardiography: Goals and Main Results , 1990, Methods of Information in Medicine.

[14]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[15]  P. Macfarlane,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, , 1990, Circulation.

[16]  Macfarlane Pw,et al.  A Brief History of Computer-Assisted Electrocardiography , 1990 .

[17]  Ewa Pietka,et al.  Feature extraction in computerized approach to the ecg analysis , 1991, Pattern Recognit..

[18]  J. Cornfield,et al.  Clinical application of a second generation electrocardiographic computer program. , 1975, The American journal of cardiology.

[19]  Y Attikiouzel,et al.  Applications of neural networks in medicine. , 1995, Australasian physical & engineering sciences in medicine.

[20]  F. N. Wilson,et al.  The potential variations produced by the heart beat at the apices of Einthoven's triangle , 1931 .

[21]  P W Macfarlane,et al.  Neural networks for classification of ECG ST-T segments. , 1992, Journal of electrocardiology.

[22]  Anthony N. Mucciardi,et al.  A Comparison of Seven Techniques for Choosing Subsets of Pattern Recognition Properties , 1971, IEEE Transactions on Computers.

[23]  Evangelia Micheli-Tzanakou,et al.  Artificial neural networks: definitions, methods, applications , 2000 .

[24]  Edward Berbari.  Principles of Electrocardiography , 1999 .

[25]  H V PIPBERGER,et al.  Automatic Recognition of Electrocardiographic Waves by Digital Computer , 1961, Circulation research.

[26]  Keinosuke Fukunaga,et al.  Application of the Karhunen-Loève Expansion to Feature Selection and Ordering , 1970, IEEE Trans. Computers.

[27]  Jin-Shiuh Taur,et al.  Prediction-based networks with ECG application , 1993, IEEE International Conference on Neural Networks.

[28]  J Cornfield,et al.  Multigroup diagnosis of electrocardiograms. , 1973, Computers and biomedical research, an international journal.

[29]  M Yokoi,et al.  Methodology of ECG interpretation in the Nagoya program. , 1990, Methods of information in medicine.

[30]  Yu Hen Hu,et al.  Training Of ECG Signals In Neural Network Pattern Recognition , 1990, [1990] Proceedings of the Twelfth Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[31]  J L Willems,et al.  Quantitative electrocardiography. Standardization and performance evaluation. , 1990, Annals of the New York Academy of Sciences.

[32]  King-Sun Fu,et al.  Selection and Ordering of Feature Observations in a Pattern Recognition System , 1968, Inf. Control..

[33]  I Rowlandson,et al.  Computerized Electrocardiography , 1990, Annals of the New York Academy of Sciences.

[34]  Richard P. Lippmann,et al.  An introduction to computing with neural nets , 1987 .

[35]  Claudio M. Held,et al.  FLAPECAN: a knowledge based system in electrocardiogram diagnosis , 1992, [1992] Proceedings Fifth Annual IEEE Symposium on Computer-Based Medical Systems.

[36]  Giovanni Bortolan,et al.  Fuzzy numbers in computerized electrocardiography , 1987 .

[37]  A. Graybiel,et al.  Recommendations for Standardization of Electrocardiographic and Vectorcardiographic Leads , 1954, Circulation.

[38]  H. Warner,et al.  Expert system diagnosis of wide complex tachycardia , 1992, Proceedings Computers in Cardiology.

[39]  R. Degani,et al.  Comparison of diagnostic results of ECG computer programs and cardiologists , 1991, [1991] Proceedings Computers in Cardiology.

[40]  A. Waller.  A Demonstration on Man of Electromotive Changes accompanying the Heart's Beat , 1887, Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc.

[41]  R Degani.  Computerized electrocardiogram diagnosis: fuzzy approach. , 1992, Methods of information in medicine.

[42]  C Brohet,et al.  Possibilities of using neural networks for ECG classification. , 1996, Journal of electrocardiology.

[43]  Giovanni Bortolan,et al.  Design Of Neural Networks For Classification Of Electrocardiographic Signals , 1990, [1990] Proceedings of the Twelfth Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[44]  P M Rautaharju,et al.  Diagnostic accuracy of the conventional 12-lead and the orthogonal Frank-lead electrocardiograms in detection of myocardial infarctions with classifiers using continuous and Bernoulli features. , 1980, Journal of electrocardiology.

[45]  A. Goldberger.  Clinical Electrocardiography: A Simplified Approach , 1977 .

[46]  P. W. MacFarlane,et al.  Trends in computer processed electrocardiograms , 1978 .

[47]  Joseph D. Bronzino,et al.  The Biomedical Engineering Handbook , 1995 .

[48]  C. Abreu-Lima,et al.  Comparison of artificial neural network based ECG classifiers using different features types , 1994, Computers in Cardiology 1994.

[49]  Ivaturi S. N. Murthy,et al.  Syntactic Approach to ECG Rhythm Analysis , 1980, IEEE Transactions on Biomedical Engineering.

[50]  C Brohet,et al.  Effect of combining electrocardiographic interpretation results on diagnostic accuracy. , 1988, European heart journal.

[51]  J. L. Willems,et al.  Diagnostic ECG classification based on neural networks. , 1993, Journal of electrocardiology.

[52]  P M Rautaharju,et al.  Selection of optimal features for classification of electrocardiograms. , 1981, Journal of electrocardiology.

[53]  P W Macfarlane.  Recent developments in computer analysis of ECGs. , 1992, Clinical physiology.

[54]  H. Wellens,et al.  Electrocardiography. Past, present, and future. , 1990, Annals of the New York Academy of Sciences.

[55]  B. Chandrasekaran,et al.  Quantization Complexity and Independent Measurements , 1974, IEEE Transactions on Computers.

[56]  C Zywietz,et al.  Signal Analysis for ECG Interpretation , 1990, Methods of Information in Medicine.

[57]  R. L. Kennedy,et al.  The early diagnosis of heart attacks: a neurocomputational approach , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.