Comparison of Different Electrocardiography with Vectorcardiography Transformations

This paper deals with transformations from electrocardiographic (ECG) to vectorcardiographic (VCG) leads. VCG provides better sensitivity, for example for the detection of myocardial infarction, ischemia, and hypertrophy. However, in clinical practice, measurement of VCG is not usually used because it requires additional electrodes placed on the patient’s body. Instead, mathematical transformations are used for deriving VCG from 12-leads ECG. In this work, Kors quasi-orthogonal transformation, inverse Dower transformation, Kors regression transformation, and linear regression-based transformations for deriving P wave (PLSV) and QRS complex (QLSV) are implemented and compared. These transformation methods were not yet compared before, so we have selected them for this paper. Transformation methods were compared for the data from the Physikalisch-Technische Bundesanstalt (PTB) database and their accuracy was evaluated using a mean squared error (MSE) and a correlation coefficient (R) between the derived and directly measured Frank’s leads. Based on the statistical analysis, Kors regression transformation was significantly more accurate for the derivation of the X and Y leads than the others. For the Z lead, there were no statistically significant differences in the medians between Kors regression transformation and the PLSV and QLSV methods. This paper thoroughly compared multiple VCG transformation methods to conventional VCG Frank’s orthogonal lead system, used in clinical practice.

[1]  Alan C. Bovik,et al.  Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures , 2009, IEEE Signal Processing Magazine.

[2]  Pablo Laguna,et al.  A database for evaluation of algorithms for measurement of QT and other waveform intervals in the ECG , 1997, Computers in Cardiology 1997.

[3]  Nandita Sharma,et al.  Visual transform applications for estimating the spatial QRS-T angle from the conventional 12-lead ECG: Kors is still most Frank. , 2014, Journal of electrocardiology.

[4]  Markus Lingman,et al.  Transient repolarization alterations dominate the initial phase of an acute anterior infarction--a vectorcardiography study. , 2014, Journal of electrocardiology.

[5]  Magnus Sederholm,et al.  The origin of monitoring of acute myocardial infarction with continuous vectorcardiography. , 2014, Journal of electrocardiology.

[6]  David M Schreck,et al.  Derivation of the 12-lead electrocardiogram and 3-lead vectorcardiogram. , 2013, The American journal of emergency medicine.

[7]  Tania Ghosal,et al.  Planarity of the spatial QRS loop of vectorcardiogram is a crucial diagnostic and prognostic parameter in acute myocardial infarction. , 2019, Medical hypotheses.

[8]  R. McFee,et al.  An orthogonal lead system for clinical electrocardiography , 1961 .

[9]  Zulpukar Kudaiberdiev,et al.  Vectorcardiographic assessment of acute hypoxia effects in pulmonary hypertension due to chronic bronchitis. , 2007, Anadolu kardiyoloji dergisi : AKD = the Anatolian journal of cardiology.

[10]  O. H. Schmitt,et al.  SYMPOSIUM ON ELECTROCARDIOGRAPHY AND VECTORCARDIOGRAPHY: The Present Status of Vectorcardiography , 1955 .

[11]  Hui Yang,et al.  Linear affine transformations between 3-lead (Frank XYZ leads) vectorcardiogram and 12-lead electrocardiogram signals. , 2009, Journal of electrocardiology.

[12]  Cecília M Costa,et al.  The association between reconstructed phase space and Artificial Neural Networks for vectorcardiographic recognition of myocardial infarction. , 2018, Journal of electrocardiology.

[13]  Ronald Rousseau,et al.  Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient , 2003, J. Assoc. Inf. Sci. Technol..

[14]  Kjell Nikus,et al.  Electrocardiographic recognition of right ventricular hypertrophy. , 2017, Journal of electrocardiology.

[15]  O. Pahlm,et al.  Vectorcardiogram synthesized from a 12-lead ECG: superiority of the inverse Dower matrix. , 1988, Journal of electrocardiology.

[16]  Luiz Carlos de Abreu,et al.  Re‐evaluating the electro‐vectorcardiographic criteria for left bundle branch block , 2019, Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc.

[17]  Michael J Ackerman,et al.  Vectorcardiography identifies patients with electrocardiographically concealed long QT syndrome. , 2017, Heart rhythm.

[18]  Tomas Peterek,et al.  Novel Method for Deriving Vectorcardiographic Leads Based on Artificial Neural Networks , 2014 .

[19]  H. C. Burger,et al.  COMPARISON OF DIFFERENT SYSTEMS OF VECTORCARDIOGRAPHY , 1952, British heart journal.

[20]  Ralf Bousseljot,et al.  Nutzung der EKG-Signaldatenbank CARDIODAT der PTB über das Internet , 2009 .

[21]  Jeffrey M. Hausdorff,et al.  Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .

[22]  Michael J Ackerman,et al.  ECG-derived spatial QRS-T angle is strongly associated with hypertrophic cardiomyopathy. , 2017, Journal of electrocardiology.

[23]  R. Granit.  THE HEART ( Extract from “ Principles and Applications of Bioelectric and Biomagnetic Fields , 2005 .

[24]  Pedro David Arini,et al.  Quaternion-based study of angular velocity of the cardiac vector during myocardial ischaemia. , 2017, International journal of cardiology.

[25]  Martin Cerný,et al.  Methods for derivation of orthogonal leads from 12-lead electrocardiogram: A review , 2015, Biomed. Signal Process. Control..

[26]  Samuel J Asirvatham,et al.  Signals and Signal Processing for the Electrophysiologist: Part II: Signal Processing and Artifact , 2011, Circulation. Arrhythmia and electrophysiology.

[27]  J.A. Malmivuo,et al.  The SVEC III vectorcardiographic lead system , 2004, IEEE Engineering in Medicine and Biology Magazine.

[28]  Samarendra Dandapat,et al.  A Weighted SVM Based Approach for Automatic Detection of Posterior Myocardial Infarction Using VCG Signals , 2019, 2019 National Conference on Communications (NCC).

[29]  Todd T Schlegel,et al.  When deriving the spatial QRS-T angle from the 12-lead electrocardiogram, which transform is more Frank: regression or inverse Dower? , 2010, Journal of electrocardiology.

[30]  P. W. Macfarlane,et al.  Vectorcardiograms synthesized from 12-lead ECGs: A new method applied in 1792 healthy children , 2004, Pediatric Cardiology.

[31]  Madhuchhanda Mitra,et al.  Automated Identification of Myocardial Infarction Using a Single Vectorcardiographic Feature , 2017, Advances in Intelligent Systems and Computing.

[32]  Ch. L. Levkov,et al.  Orthogonal electrocardiogram derived from the limb and chest electrodes of the conventional 12-lead system , 1987, Medical and Biological Engineering and Computing.

[33]  E. Fischmann,et al.  EXPERIMENTAL COMPARISON OF "PARALLEL GRID LEADS" WITH SIMPLE BIPOLAR, AND THE SVEC-III, FRANK, AND MCFEE-PARUNGAO SYSTEMS. I. SAGITTAL LEADS. , 1965, American heart journal.

[34]  O. H. Schmitt,et al.  The present status of vectorcardiography. , 1955, A.M.A. archives of internal medicine.

[35]  A. Sittig,et al.  Reconstruction of the Frank vectorcardiogram from standard electrocardiographic leads: diagnostic comparison of different methods. , 1990, European heart journal.

[36]  E. Sowton.  Primer of Vectorcardiography , 1973 .

[37]  Pedro David Arini,et al.  Comparison of Electrocardiographic and Vectorcardiographic Planes on a Set of Left Ventricular Hypertrophy Patients , 2015 .

[38]  Samuel J Asirvatham,et al.  Signals and signal processing for the electrophysiologist: part I: electrogram acquisition. , 2011, Circulation. Arrhythmia and electrophysiology.

[39]  Y. Ito.  [Ischemic heart disease]. , 1966, Saishin igaku. Modern medicine.

[40]  Amit Acharyya,et al.  Frank vectorcardiographic system from standard 12 lead ECG: An effort to enhance cardiovascular diagnosis. , 2016, Journal of electrocardiology.

[41]  Hung T. Nguyen,et al.  Fundamentals of mathematical statistics , 1989 .

[42]  H. Koymen,et al.  SVD-based on-line exercise ECG signal orthogonalization , 1999, IEEE Transactions on Biomedical Engineering.

[43]  S. Dandapat,et al.  Detection of myocardial infarction from vectorcardiogram using relevance vector machine , 2017, Signal Image Video Process..

[44]  Lars Edenbrandt,et al.  12 LEAD VECTORCARDIOGRAPHY , 1995 .

[45]  J A Kors,et al.  Combination of diagnostic classifications from ECG and VCG computer interpretations. , 1992, Journal of electrocardiology.

[46]  F. Buendía-Fuentes,et al.  High-Bandpass Filters in Electrocardiography: Source of Error in the Interpretation of the ST Segment , 2012, ISRN cardiology.

[47]  S. Swiryn,et al.  Derivation of orthogonal leads from the 12-lead ECG. accuracy of a single transform for the derivation of atrial and ventricular waves , 2006, 2006 Computers in Cardiology.

[48]  P Rubel,et al.  Quantitative assessment of eight different methods for synthesizing Frank VCGs from simultaneously recorded standard ECG leads. , 1992, Journal of electrocardiology.

[49]  Francisco Castells,et al.  Limitations of Dower's Inverse Transform for the Study of Atrial Loops during Atrial Fibrillation , 2009, Pacing and clinical electrophysiology : PACE.

[50]  J.A. Hyttinen,et al.  Optimization and comparison of derived Frank VECG lead systems employing an accurate thorax model , 1995, Computers in Cardiology 1995.