Abstract
The electrocardiogram (ECG) is a representative signal containing information about the condition of the heart. The shape and size of the P-QRS-T wave, the time intervals between its various peaks, may contain useful information about the nature of disease afflicting the heart. However, these subtle details cannot be directly monitored by the human observer. Besides, these signals are highly subjective, and the symptoms may appear at random in the time scale. It is very taxing and time-consuming to decipher cardiac abnormalities based on these ECG signals. The Vectorcardiogram (VCG) is the vector loop in the 2-D frontal plane, indicating the magnitude and direction of the instantaneous heart electrical activity vector (HAV), which represents the sum of the dipole vectors located along the instantaneous depolarization wavefront. The HAV is constructed from the monitored 3-lead ECG signals, placed at the three vertices of the modified Einthoven triangle formed by the 3-lead system in the frontal plane of the torso. The VCG examines the electrical activities within the heart, using the ECG signals along the three sides of the modified Einthoven triangle, and displays electrical events in the 2-dimensional frontal plane. This study demonstrates the development of the heart-depolarisation vector-locus cardiogram (using modified Einthoven’s triangle), as a diagnostic measure of the left ventricular depolarisation strength. Our work involves the reconstruction of the “equivalent heart vector” for the QRS complex from limb lead voltages of a sample ECG, and plotting the progression of the cardiac vector during the QRS complex. We have demonstrated the construction of the frontal plane heart-depolarization vector cardiogram (HDVC), as the path of the locus of the tip of the heart electrical activity vector, with initial and terminal points at the origin. In this work, we have shown characteristic patterns of HDVC for cardiac states namely, normal, bundle branch block, ventricular hypertrophy and myocardial infarction. We have demonstrated how HDVC can be diagnostically employed to characterize cardiac disorders, such as ventricular hypertrophy bundle branch block and inferior myocardial infarction.
Similar content being viewed by others
References
Acharya, U. R., Spaan, J. A. E., and Suri, J. S., Advances in Cardiac Signal Processing. GmbH Berlin Heidelberg: Springer Verlang, 2007. ISBN:978-3-540-36674-4.
Astrom, M., Santos, E. C., Sornmo, L., Laguna, P., and Wohlfart, B., Vectorcardiographic Loop Alignment and the Measurement of Morphologic Beat-to-Beat Variability in Noisy Signals. IEEE Trans. Biomed. Eng. 47(4):497–506, 2000.
Atarashi, H., Ogawa, S., and Harumi, K., Idiopathic Ventricular Fibrillation Investigators. Three-year follow-up of patients with right bundle branch block and ST segment elevation in the right precordial leads: Japanese Registry of Brugada Syndrome. Idiopathic Ventricular Fibrillation Investigators. J. Am. Coll. Cardiology. 37:1916–1920, 2001.
Benchimol, A., Desser, K. B., and Schumacher, J., Left anterior hemiblock from inferior infarction with left axis deviation. Chest. 61:74–76, 1972.
Benchimol, A., and Desser, K. B., Advances in clinical vectorcardiography. Am. J. Cardiol. 36:76–86, 1975.
Carson, W., Tseng, Y. Z., Tseng, C. D., Huang, P. J., and Wu, T. L., Vectorcardiographic criteria for acute right ventricular infarction. Eur. Heart J. 9(9):955–96, 1, 1988.
Chee, J., Acharya, U. R., Kenneth, Er., Tan, W., and Chua, K. C., Visualization of cardiac health using vector cardiogram. Innovations and Technology in Biology and Medicine (ITBM-RBM), 2008 (In Press).
Chia, J. M., Fischer, S. E., Wickline, S. A., and Lorenz, C. H., Performance of QRS detection for cardiac magnetic resonance imaging with a novel vectorcardiographic triggering method. J. Magn. Reson. Imaging. 12(5):678–688, 2000.
Chou, T. C., Value and limitations of vectorcardiography in cardiac diagnosis. Cardiovasc. Clin. 6:163–178, 1975.
Chou, T. C., When is the vectorcardiogram superior to the scalar electrocardiogram? J. Am. Coll. Cardiol. 8:791–799, 1986.
Dahlin, L. G., Ebeling-Barbier, C., Nylander, E., Rutberg, H., and Svedjeholm, R., Vectorcardiography is Superior to Conventional ECG for Detection of Myocardial Injury after Coronary Surgery. Scand. Cardiovasc. J. 35(2):125–128, 2001.
Dower, G. E., Machado, H. B., and Osborne, J. A., On Deriving the Electrocardiogram from Vectocardiographic Leads. Clin. Cardiol. 3:87–95, 1980.
Downs, T., Liebman, J., and Mackay, W., Statistical methods for vectorcardiogram orientations. In: Hoffman, I., Hamby, R. I., and Glassman, E., (Eds.), Vectorcardiography 2: Proc. XIth International Symposium on Vectorcardiography. pp. 216–222, 1971.
Edenbrandt, L., and Pahlm, O., Vectorcardiogram synthesized from a 12-lead ECG: superiority of the inverse Dower matrix. J. Electrocardiol. 21(4):361–367, 1988.
Eriksson, P., Andersen, K., Swedberg, K., and Dellborg, M., Vectorcardiographic monitoring of patients with acute myocardial infarction and chronic bundle branch block. Eur. Heart J. 18(8):1288–1295, 1997.
Fedor, J. M., Walston, A., Wagner, G. S., and Starr, J., The vectorcardiogram in right bundle branch block: correlation with cardiac failure and pulmonary disease. Circulation. 53(6):926–930, 1976.
Ghista, D. N., Van Vollenhoven, E., Yang, W. J., Reul, H., and Bleifeld, W., Cardiovascular Engineering Part 3: Diagnosis. Karger, 1983. ISBN: 978-3-8055-3611-0.
Grishman, A., and Donoso, E., Spatial vectorcardiography II. Mod. Concepts Cardiovasc. Dis. 30:693–696, 1961.
Guo, X., Jue, X., and Ruan, Y., Model TJ-IV Computer-assisted vectorcardiogram analysis system. J. Tongji. Med. Univ. 21:22–81, 2001.
Guo, X. M., Que, X. H., Ma, Y. X., and Wang, Z. C., Development and applications of an auto-analyzing system for model TJ-IV vector-cardiogram. Zhongguo Yi Liao Qi Xie Za Zhi. 29(1):19–22, 2005.
http://www.cdc.gov/nchs/data/hestat/leadingdeaths03_tables.pdf (Last accessed on April 2008).
http://www.ptb.de/index_en.html (Last accessed on May 2008).
Hurd, H. P., Starling, M. R., and Crawford, M. H., Comparative accuracy of electrocardiographic and vectorcardiographic criteria for inferior myocardial infarction. Circulation. 63:1025–1029, 1981.
Huszar, R. J., Basic Dysrhythmias. Interpretation & Management, 3rd ed. St. Louis, Mo: Mosby, Inc, 2002.
Ikeda, K., Takahashi, K., and Yasui, S., Assessment of right ventricular overload in patients with chronic pulmonary disease by 12-lead electrocardiography, vectorcardiography and body surface electrocardiographic mapping. Jpn. Circ. J. 53(10):1278–1286, 1989.
Jens, J., Sven, V. E., Bo, L., Peter, L., and Christer, S., On-line vectorcardiography during elective coronary angioplasty indicates procedure-related myocardial infarction. Coronary Artery Disease. 11(2):161–169, 2000.
Kawahito, S., Kitahata, H., Tanaka, K., Nozaki, J., and Oshita, S., Dynamic QRS-complex and ST-segment monitoring by continuous vectorcardiography during carotid endarterectomy. Br. J. Anaesth. 90(2):142–147, 2003.
Lynn, P. A., Online Digital Filter for Biological Signals: Some Fast Designs for a small computer. Med. Biol. Eng. Comput. 15(5):534–540, 1977.
Malmivuo, J., and Plonsey, R., Bioelectromagnetism: Principles and Applications of Bioelectric and Biomagnetic Field0073. New York: Oxford University Press, 1995a.
Malmivuo, J., and Plonsey, R., Bioelectromagnetism: Principles and Applications of Bioelectric and Biomagnetic Field0073. New York: Oxford University Press, 1995b. Chapter 16.
McConahay, D. R., McCallister, B. D., Hallermann, F. J., and Smith, R. E., Comparative quantitative analysis of the electrocardiogram and the vectorcardiogram Correlations with the coronary arteriogram. Circulation. 42(2):245–259, 1970.
Nakos, A., and Joyner, D., Linear algebra with Applications. Brooks/Cole Pub Co., 1998
Rautaharju, P. M., A hundred years of progress in electrocardiography. 2: The rise and decline of vectorcadiography. Can. J. Cardiol. 4:60–71, 1998.
Reddy, B. R. S., Murthy, I. S. N., and Chatterjee, P. C., Rhythm Analysis Using Vectorcardiograms. IEEE Trans.Biomed. Eng. 32(2):97–104, 1985.
Riera, A. R. P., Uchida, A. H., Filho, C. F., Meneghini, A., Ferreira, C., Schapacknik, E., Dubner, S., and Moffa, P., Significance of Vectorcardiogram in the Cardiological Diagnosis of the 21st Century. Clin. Cardiol. 30(7):319–323, 2007.
Sokolow, M., Mcllroy, M. B., and Chiethin, M. D., Clinical cardiology. Stamford, CT: Appleton & Lange medical book, 1990. ISBN:978-0838510933.
Tompkins, W. J., Biomedical Signal Processing. Englewood Cliffs, NJ: Prentice Hall, 1993.
van Oosterom, A., Ihara, Z., Jacquemet, V., and Hoekema, R., Vectorcardiographic lead systems for the characterization of atrial fibrillation. J. Electrocardiol. 40(4):343.e1–343.e11, 2007.
Vine, D. L., Finchum, R. N., Dodge, H. T., Bancroft, W. H. Jr, and Hurst, D. C., Comparison of the vectorcardiogram with the electrocardiogram in the prediction of left ventricular size. Circulation. 43(4):547–558, 1971.
Wariar, R., and Eswaran, C., Integer coefficient bandpass filter for the simultaneous removal of baseline wander, 50 and 100 Hz interference from the ECG. Med. Biol. Eng. Comput. 29(3):333–336, 1991.
Watanabe, Y., Wang, J., Kondo, T., Tokuda, M., Chikamatsu, H., Yasui, T., Yamaguchi, T., Kinoshita, M., Kamide, S., Nagai, N., Abo, Y., Yokoi, H., and Hishida, H., Vectorcardiographic evaluation of myocardial infarct size: departure parameters are superior to conventional spatial parameters. Jpn. Circ. J. 62(7):473–478, 1998.
Young, E., Levine, H. D., Vokonas, P. S., Kemp, H. G., Williams, R. A., and Gorlin, R., The frontal plane vectorcardiogram in old inferior myocardial infarcton II. Mid-to-late QRS changes. Circulation. 42(6):1143–1162, 1970.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Ghista, D.N., Acharya, U.R. & Nagenthiran, T. Frontal Plane Vectorcardiograms: Theory and Graphics Visualization of Cardiac Health Status. J Med Syst 34, 445–458 (2010). https://doi.org/10.1007/s10916-009-9257-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10916-009-9257-x