Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Biomedical Engineering / Biomedizinische Technik

Joint Journal of the German Society for Biomedical Engineering in VDE and the Austrian and Swiss Societies for Biomedical Engineering and the German Society of Biomaterials

Editor-in-Chief: Dössel, Olaf

Editorial Board: Augat, Peter / Habibović, Pamela / Haueisen, Jens / Jahnen-Dechent, Wilhelm / Jockenhoevel, Stefan / Knaup-Gregori, Petra / Lenarz, Thomas / Leonhardt, Steffen / Plank, Gernot / Radermacher, Klaus M. / Schkommodau, Erik / Stieglitz, Thomas / Boenick, Ulrich / Jaramaz, Branislav / Kraft, Marc / Lenthe, Harry / Lo, Benny / Mainardi, Luca / Micera, Silvestro / Penzel, Thomas / Robitzki, Andrea A. / Schaeffter, Tobias / Snedeker, Jess G. / Sörnmo, Leif / Sugano, Nobuhiko / Werner, Jürgen /


IMPACT FACTOR 2018: 1.007
5-year IMPACT FACTOR: 1.390

CiteScore 2018: 1.24

SCImago Journal Rank (SJR) 2018: 0.282
Source Normalized Impact per Paper (SNIP) 2018: 0.831

Online
ISSN
1862-278X
See all formats and pricing
More options …
Volume 61, Issue 1

Issues

Volume 57 (2012)

A review of beat-to-beat vectorcardiographic (VCG) parameters for analyzing repolarization variability in ECG signals

Muhammad A. Hasan
  • Corresponding author
  • Department of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA 5005, Australia
  • Centre for Biomedical Engineering (CBME), The University of Adelaide, Adelaide, SA 5005, Australia
  • Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Derek Abbott
  • Department of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA 5005, Australia
  • Centre for Biomedical Engineering (CBME), The University of Adelaide, Adelaide, SA 5005, Australia
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2015-05-20 | DOI: https://doi.org/10.1515/bmt-2015-0005

Abstract

Elevated ventricular repolarization lability is believed to be linked to the risk of ventricular tachycardia/ventricular fibrillation. However, ventricular repolarization is a complex electrical phenomenon, and abnormalities in ventricular repolarization are not completely understood. To evaluate repolarization lability, vectorcardiography (VCG) is an alternative approach where the electrocardiographic (ECG) signal can be considered as possessing both magnitude and direction. Recent research has shown that VCG is advantageous over ECG signal analysis for identification of repolarization abnormality. One of the key reasons is that the VCG approach does not rely on exact identification of the T-wave offset, which improves the reproducibility of the VCG technique. However, beat-to-beat variability in VCG is an emerging area for the investigation of repolarization abnormality though not yet fully realized. Therefore, the purpose of this review is to explore the techniques, findings, and efficacy of beat-to-beat VCG parameters for analyzing repolarization lability, which may have potential utility for further study.

Keywords: electrocardiography (ECG); QT interval variability; repolarization; vector electrocardiogram (VCG)

References

  • [1]

    Abdelraheem M, Selim H, Abdelhamid TK. Human identification using the main loop of the vectorcardiogram. Am J Signal Process 2012; 2: 23–29.CrossrefGoogle Scholar

  • [2]

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

  • [3]

    Acar B, Yi G, Hnatkova K, Malik M. Spatial, temporal and wavefront direction characteristics of 12-lead T-wave morphology. Med Biol Eng Comput 1999; 37: 574–584.Google Scholar

  • [4]

    Aro AL, Huikuri HV, Tikkanen JT, et al. QRS-T angle as a predictor of sudden cardiac death in a middle-aged general population. Europace 2012; 14: 872–876.CrossrefGoogle Scholar

  • [5]

    Astrom M, Santos EC, Sörnmo L, Laguna P, Wohlfart B. Vectorcardiographic loop alignment and the measurement of morphologic beat-to-beat variability in noisy signals. IEEE Trans Biomed Eng 2000; 47: 497–506.CrossrefGoogle Scholar

  • [6]

    Bailón R, Sörnmo L, Laguna P. A robust method for ECG-based estimation of the respiratory frequency during stress testing. IEEE Trans Biomed Eng 2006; 53: 1273–1285.Google Scholar

  • [7]

    Batchvarov V, Dilaveris P, Färbom P, et al. New descriptors of homogeneity of the propagation of ventricular repolarization. PACE 2000; 23: 1968–1972.CrossrefGoogle Scholar

  • [8]

    Batchvarov VN, Hnatkova K, Poloniecki J, Camm AJ, Malik M. Prognostic value of heterogeneity of ventricular repolarization in survivors of acute myocardial infarction. Clin Cardiol 2004; 27: 653–659.CrossrefGoogle Scholar

  • [9]

    Beckerman J, Yamazaki T, Myers J, et al. T-Wave abnormalities are a better predictor of cardiovascular mortality than ST depression on the resting electrocardiogram. Ann Noninvasive Electrocardiol 2005; 10: 146–151.Google Scholar

  • [10]

    Berger RD, Kasper EK, Baughman KL, Marban E, Calkins H, Tomaselli GF. Beat-to-beat QT interval variability: novel evidence for repolarization lability in ischemic and nonischemic dilated cardiomyopathy. Circulation 1997; 96: 1557–1565.CrossrefGoogle Scholar

  • [11]

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

  • [12]

    Carlson J, Havmoller R, Herreros A, Platonov P, Johansson R, Olsson B. Can orthogonal lead indicators of propensity to atrial fibrillation be accurately assessed from the 12-lead ECG? Europace 2005; 7: S39–S48.CrossrefGoogle Scholar

  • [13]

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

  • [14]

    Correa R, Arini PD, Correa LS, Valentinuzzi M, Laciar E. Novel technique for ST-T interval characterization in patients with acute myocardial ischemia. Comput Biol Med 2014; 50: 49–55.CrossrefGoogle Scholar

  • [15]

    Correa R, Arini PD, Valentinuzzi ME, Laciar E. Novel set of vectorcardiographic parameters for the identification of ischemic patients. Med Eng Phys 2013; 35: 16–22.CrossrefGoogle Scholar

  • [16]

    Correa R, Laciar E, Arini P, Jané R. Analysis of QRS loop in the vectorcardiogram of patients with Chagas’ disease. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2010: 2561–2564.Google Scholar

  • [17]

    Couderc J-P. Cardiac regulation and electrocardiographic factors contributing to the measurement of repolarization variability. J Electrocardiol 2009; 42: 494–499.CrossrefGoogle Scholar

  • [18]

    Critchley HD, Taggart P, Sutton PM, et al. Mental stress and sudden cardiac death: asymmetric midbrain activity as a linking mechanism. Brain 2005; 128: 75–85.Google Scholar

  • [19]

    Dahlin L-G, Ebeling-Barbier C, Nylander E, Rutberg H, Svedjeholm R. Vectorcardiography is superior to conventional ECG for detection of myocardial injury after coronary surgery. Scand Cardiovasc J 2001; 35: 125–128.Google Scholar

  • [20]

    Daskalov I, Christov I. Automatic detection of the electrocardiogram T-wave end. Med Biol Eng Comput 1999; 37: 348–353.Google Scholar

  • [21]

    Dilaveris P, Roussos D, Giannopoulos G, et al. Clinical determinants of electrocardiographic and spatial vectorcardiographic descriptors of ventricular repolarization in healthy children. Ann Noninvasive Electrocardiol 2011; 16: 49–55.Google Scholar

  • [22]

    Dower GE, Machado HB, Osborne J. On deriving the electrocardiogram from vectoradiographic leads. Clin Cardiol 1980; 3: 87.Google Scholar

  • [23]

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

  • [24]

    Edenbrandt L, Jonson B, Lundh B, Pahlm O. Sex- and age-related normal limits for the QRS complex in vectorcardiography. Clin Physiol 1987; 7: 525–536.CrossrefGoogle Scholar

  • [25]

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

  • [26]

    Friedman HS. Determinants of the total cosine of the spatial angle between the QRS complex and the T-wave (TCRT): implications for distinguishing primary from secondary T-wave abnormalities. J Electrocardiol 2007; 40: 12–17.CrossrefGoogle Scholar

  • [27]

    Gang Y, Hnatkova K, Guo X, et al. Reproducibility of T-wave morphology assessment in patients with hypertrophic cardiomyopathy and in healthy subjects. Comput Cardiol 2001; 393–396.Google Scholar

  • [28]

    Giorgi C, Nadeau R, Primeau R, et al. Comparative accuracy of the vectorcardiogram and electrocardiogram in the localization of the accessory pathway in patients with Wolff-Parkinson-White syndrome: validation of a new vectorcardiographic algorithm by intraoperative epicardial mapping and electrophysiologic studies. Am Heart J 1990; 119(Pt 1): 592–598.Google Scholar

  • [29]

    Goldenberg I, Mathew J, Moss AJ, et al. Corrected QT variability in serial electrocardiograms in long QT syndrome the importance of the maximum corrected QT for risk stratification. J Am Coll Cardiol 2006; 48: 1047–1052.CrossrefGoogle Scholar

  • [30]

    Gregory TS, Schmidt EJ, Zhang SH, Ho Tse ZT. 3DQRS: a method to obtain reliable QRS complex detection within high field MRI using 12-lead electrocardiogram traces. Magn Reson Med 2014; 71: 1374–1380.Google Scholar

  • [31]

    Grishman A, Donoso E. Spatial vectorcardiography. II. Mod Concepts Cardiovasc Dis 1961; 30: 693–696.Google Scholar

  • [32]

    Guillem MS, Climent AM, Bollmann A, Husser D, Millet J, Castells F. Limitations of Dower’s inverse transform for the study of atrial loops during atrial fibrillation. PACE 2009; 32: 972–980.CrossrefGoogle Scholar

  • [33]

    Guillem MS, Sahakian AV, Swiryn S. Derivation of orthogonal leads from the 12-lead electrocardiogram. Performance of an atrial-based transform for the derivation of P loops. J Electrocardiol 2008; 41: 19–25.CrossrefGoogle Scholar

  • [34]

    Guller B, Lau FY, Dunn RF, Pipberger HA, Pipberger HV. Computer analysis of changes in Frank vectorcardiograms of 666 normal infants in the first 72 hours of life. J Electrocardiol 1977; 10: 19–26.Google Scholar

  • [35]

    Han L, Tereshchenko LG. Lability of R-and T-wave peaks in three-dimensional electrocardiograms in implantable cardioverter defibrillator patients with ventricular tachyarrhythmia during follow-up. J Electrocardiol 2010; 43: 577–582.CrossrefGoogle Scholar

  • [36]

    Hasan M, Reaz M. Hardware prototyping of neural network based fetal electrocardiogram extraction. Meas Sci Rev 2012; 12: 52–55.Google Scholar

  • [37]

    Hasan MA, Abbott D, Baumert M. Beat-to-beat QT interval variability in the 12 lead ECG. Comput Cardiol 2011; 61–64.Google Scholar

  • [38]

    Hasan MA, Abbott D, Baumert M. Beat-to-beat spatial and temporal analysis for QRS-T morphology. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2012: 4193–4195.CrossrefGoogle Scholar

  • [39]

    Hasan MA, Abbott D, Baumert M. Beat-to-beat vectorcardiographic analysis of ventricular depolarization and repolarization in myocardial infarction. PLoS One 2012; 7: e49489.PubMedGoogle Scholar

  • [40]

    Hasan MA, Abbott D, Baumert M. Relation between beat-to-beat QT interval variability and T-Wave amplitude in healthy subjects. Ann Noninvasive Electrocardiol 2012; 17: 195–203.Google Scholar

  • [41]

    Hasan MA, Abbott D, Baumert M. Beat-to-beat QT interval variability and T-wave amplitude in patients with myocardial infarction. Physiol Meas 2013; 34: 1075–1083.PubMedCrossrefGoogle Scholar

  • [42]

    Hinterseer M, Thomsen MB, Beckmann B-M, et al. Beat-to-beat variability of QT intervals is increased in patients with drug-induced long-QT syndrome: a case control pilot study. Eur Heart J 2008; 29: 185–190.CrossrefGoogle Scholar

  • [43]

    Huang HC, Lin LY, Yu HY, Ho YL. Risk stratification by T-wave morphology for cardiovascular mortality in patients with systolic heart failure. Europace 2009; 11: 1522–1528.CrossrefGoogle Scholar

  • [44]

    Kania M, Fereniec M, Janusek D, et al. Optimal ECG lead system for arrhythmia assessment with use of TCRT parameter. Biocybern Biomed Eng 2009; 29: 75–82.Google Scholar

  • [45]

    Kardys I, Kors JA, van der Meer IM, Hofman A, van der Kuip DA, Witteman JC. Spatial QRS-T angle predicts cardiac death in a general population. Eur Heart J 2003; 24: 1357–1364.CrossrefGoogle Scholar

  • [46]

    Karsikas M, Huikuri H, Seppanen T. Improving reliability of “total-cosine-R-to-T” (TCRT) in patients with acute myocardial infarction. Comput Cardiol 2008; 373–376.Google Scholar

  • [47]

    Karsikas M, Noponen K, Tulppo M, Huikuri HV, Seppanen T. Beat-to-beat variation of three-dimensional QRS-T angle measures during exercise test. Comput Cardiol 2009; 125–128.Google Scholar

  • [48]

    Kautzner J, Yi G, Camm A, Malik M. Short-and long-term reproducibility of QT, QTc, and QT dispersion measurement in healthy subjects. PACE 1994; 17: 928–937.CrossrefGoogle Scholar

  • [49]

    Kenttä T, Karsikas M, Junttila MJ, et al. QRS-T morphology measured from exercise electrocardiogram as a predictor of cardiac mortality. Europace 2011; 13: 701–707.CrossrefGoogle Scholar

  • [50]

    Kenttä T, Karsikas M, Kiviniemi A, Tulppo M, Seppänen T, Huikuri HV. Dynamics and rate-dependence of the spatial angle between ventricular depolarization and repolarization wave fronts during exercise ECG. Ann Noninvasive Electrocardiol 2010; 15: 264–275.Google Scholar

  • [51]

    Koivikko M, Karsikas M, Salmela P, et al. Effects of controlled hypoglycaemia on cardiac repolarisation in patients with type 1 diabetes. Diabetologia 2008; 51: 426–435.Google Scholar

  • [52]

    Kors J, van Herpen G. Measurement error as a source of QT dispersion: a computerised analysis. Heart 1998; 80: 453–458.CrossrefGoogle Scholar

  • [53]

    Kors JA, Kardys I, van der Meer IM, et al. Spatial QRS-T angle as a risk indicator of cardiac death in an elderly population. J Electrocardiol 2003; 36: 113–114.CrossrefGoogle Scholar

  • [54]

    Kors JA, Van Herpen G, Sittig AC, Van Bemmel JH. Reconstruction of the Frank vectorcardiogram from standard electrocardiographic leads: diagnostic comparison of different methods. Eur Heart J 1990; 11: 1083–1092.CrossrefGoogle Scholar

  • [55]

    Krug J, Rose G, Stucht D, Clifford G, Oster J. Limitations of VCG based gating methods in ultra high field cardiac MRI. J Cardiovasc Magn Reson 2013; 15(Suppl 1): W19.Google Scholar

  • [56]

    Laguna P, Thakor N, Caminal P, et al. New algorithm for QT interval analysis in 24-hour Holter ECG: performance and applications. Med Biol Eng Comput 1990; 28: 67–73.Google Scholar

  • [57]

    Leanderson S, Laguna P, Sörnmo L. Estimation of the respiratory frequency using spatial information in the VCG. Med Eng Phys 2003; 25: 501–507.CrossrefGoogle Scholar

  • [58]

    Lin CY, Lin LY, Chen PC. Analysis of T-wave morphology from the 12-lead electrocardiogram for prediction of long-term prognosis in patients initiating haemodialysis. Nephrol Dialysis Transplant 2007; 22: 2645–2652.CrossrefGoogle Scholar

  • [59]

    Lin YH, Lin LY, Chen YS, et al. The association between T-wave morphology and life-threatening ventricular tachyarrhythmias in patients with congestive heart failure. PACE 2009; 32: 1173–1177.CrossrefGoogle Scholar

  • [60]

    Lingman M, Hartford M, Karlsson T, et al. Transient repolarization alterations dominate the initial phase of an acute anterior infarction-a vectorcardiography study. J Electrocardiol 2014; 47: 478–485.CrossrefGoogle Scholar

  • [61]

    Malik M, Hnatkova K, Batchvarov VN. Post infarction risk stratification using the 3-D angle between QRS complex and T-wave vectors. J Electrocardiol 2004; 37(Suppl): 201–208.Google Scholar

  • [62]

    Malmivuo J, Plonsey R. Bioelectromagnetism: principles and applications of bioelectric and biomagnetic fields. Oxford: Oxford University Press 1995.Google Scholar

  • [63]

    Man S, van Zwet E, Maan A, Schalij M, Swenne C. Individually improved VCG synthesis. Comput Cardiol 2009; 277–280.Google Scholar

  • [64]

    Maredia N, Radjenovic A, Kozerke S, Larghat A, Greenwood JP, Plein S. Effect of improving spatial or temporal resolution on image quality and quantitative perfusion assessment with k-t SENSE acceleration in first-pass CMR myocardial perfusion imaging. Magn Reson Med 2010; 64: 1616–1624.CrossrefGoogle Scholar

  • [65]

    Mikio S, Inden Y, Sawada T, et al. Comparison of vectorcardiographic and 12-lead electrocardiographic detections of abnormalities in repolarization properties due to preexcitation in patients with Wolff-Parkinson-White syndrome. Jpn Heart J 2000; 41: 295–312.CrossrefGoogle Scholar

  • [66]

    Murabayashi T, Fetics B, Kass D, Nevo E, Gramatikov B, Berger RD. Beat-to-beat QT interval variability associated with acute myocardial ischemia. J Electrocardiol 2002; 35: 19–25.CrossrefGoogle Scholar

  • [67]

    Perkiömäki JS, Hyytinen-Oinas M, Karsikas M, et al. Usefulness of T-wave loop and QRS complex loop to predict mortality after acute myocardial infarction. Am J Cardiol 2006; 97: 353–360.CrossrefGoogle Scholar

  • [68]

    Porthan K, Viitasalo M, Jula A, et al. Predictive value of electrocardiographic QT interval and T-wave morphology parameters for all-cause and cardiovascular mortality in a general population sample. Heart Rhythm 2009; 6: 1202–1208.CrossrefGoogle Scholar

  • [69]

    Potter SLP, Holmqvist F, Platonov PG, et al. Detection of hypertrophic cardiomyopathy is improved when using advanced rather than strictly conventional 12-lead electrocardiogram. J Electrocardiol 2010; 43: 713–718.CrossrefGoogle Scholar

  • [70]

    Priori SG, Mortara DW, Napolitano C, et al. Evaluation of the spatial aspects of T-wave complexity in the long-QT syndrome. Circulation 1997; 96: 3006–3012.Google Scholar

  • [71]

    Priori SG, Schwartz PJ, Napolitano C, et al. Risk stratification in the long-QT syndrome. N Engl J Med 2003; 348: 1866–1874.Google Scholar

  • [72]

    Raghunandan D, Desai N, Mallavarapu M, Berger RD, Yeragani VK. Increased beat-to-beat QT variability in patients with congestive cardiac failure. Ind Heart J 2004; 57: 138–142.Google Scholar

  • [73]

    Rautaharju PM, Warren J, Wolf H. Waveform vector analysis of orthogonal electrocardiograms: quantification and data reduction. J Electrocardiol 1973; 6: 103–111.CrossrefGoogle Scholar

  • [74]

    Riekkinen H, Rautaharju P. Body position, electrode level, and respiration effects on the Frank lead electrocardiogram. Circulation 1976; 53: 40–45.CrossrefGoogle Scholar

  • [75]

    Rubulis A, Jensen SM, Näslund U, Lundahl G, Jensen J, Bergfeldt L. Ischemia-induced repolarization response in relation to the size and location of the ischemic myocardium during short-lasting coronary occlusion in humans. J Electrocardiol 2010; 43: 104–112.CrossrefGoogle Scholar

  • [76]

    Scherptong RW, Henkens IR, Man SC, et al. Normal limits of the spatial QRS-T angle and ventricular gradient in 12-lead electrocardiograms of young adults: dependence on sex and heart rate. J Electrocardiol 2008; 41: 648–655.CrossrefGoogle Scholar

  • [77]

    Schreck DM, Fishberg RD. Derivation of the 12-lead electrocardiogram and 3-lead vectorcardiogram. Am J Emerg Med 2013; 31: 1183–1190.CrossrefGoogle Scholar

  • [78]

    Shvilkin A, Bojovic B, Vajdic B, Gussak I, Zimetbaum P, Josephson ME. Vectorcardiographic determinants of cardiac memory during normal ventricular activation and continuous ventricular pacing. Heart Rhythm 2009; 6: 943–948.CrossrefGoogle Scholar

  • [79]

    Shvilkin A, Bojovic B, Vajdic B, et al. Vectorcardiographic and electrocardiographic criteria to distinguish new and old left bundle branch block. Heart Rhythm 2010; 7: 1085–1092.CrossrefGoogle Scholar

  • [80]

    Smetana P, Batchvarov VN, Hnatkova K, Camm AJ, Malik M. Sex differences in repolarization homogeneity and its circadian pattern. Am J Physiol Heart Circul Physiol 2002; 282: H1889–H1897.Google Scholar

  • [81]

    Sörnmo L. Vectorcardiographic loop alignment and morphologic beat-to-beat variability. IEEE Trans Biomed Eng 1998; 45: 1401–1413.CrossrefGoogle Scholar

  • [82]

    Sotobata I, Richman H, Simonson E, Fukomoto A. Sex differences in the vectorcardiogram. Circulation 1968; 37: 438–448.Google Scholar

  • [83]

    Sovilj S, Magjarević R, Lovell NH, Dokos S. A simplified 3D model of whole heart electrical activity and 12-lead ECG generation. Comput Math Methods Med 2013; 2013: 1–10.CrossrefGoogle Scholar

  • [84]

    Strauss DG, Olson CW, Wu KC, et al. Vectorcardiogram synthesized from the 12-lead electrocardiogram to image ischemia. J Electrocardiol 2009; 42: 190–197.CrossrefGoogle Scholar

  • [85]

    Sur S, Han L, Tereshchenko LG. Comparison of sum absolute QRST integral, and temporal variability in depolarization and repolarization, measured by dynamic vectorcardiography approach, in healthy men and women. PLoS One 2013; 8: e57175.Google Scholar

  • [86]

    Tereshchenko LG, Han L, Cheng A, et al. Beat-to-beat three-dimensional ECG variability predicts ventricular arrhythmia in ICD recipients. Heart Rhythm 2010; 7: 1606–1613.CrossrefGoogle Scholar

  • [87]

    Turrini P, Corrado D, Basso C, Nava A, Bauce B, Thiene G. Dispersion of ventricular depolarization-repolarization a noninvasive marker for risk stratification in arrhythmogenic right ventricular cardiomyopathy. Circulation 2001; 103: 3075–3080.Google Scholar

  • [88]

    Vahedi F, Haney MF, Jensen SM, Näslund U, Bergfeldt L. Effect of heart rate on ventricular repolarization in healthy individuals applying vectorcardiographic T vector and T vector loop analysis. Ann Noninvasive Electrocardiol 2011; 16: 287–294.Google Scholar

  • [89]

    Vahedi F, Odenstedt J, Hartford M, Gilljam T, Bergfeldt L. Vectorcardiography analysis of the repolarization response to pharmacologically induced autonomic nervous system modulation in healthy subjects. J Appl Physiol 2012; 113: 368–376.Google Scholar

  • [90]

    Villongco CT, Krummen DE, Stark P, Omens JH, McCulloch AD. Patient-specific modeling of ventricular activation pattern using surface ECG-derived vectorcardiogram in bundle branch block. Progr Biophys Mol Biol 2014; 115: 305–313.Google Scholar

  • [91]

    Vullings R, Mischi M, Oei SG, Bergmans JWM. Novel Bayesian vectorcardiographic loop alignment for improved monitoring of ECG and fetal movement. IEEE Trans Biomed Eng 2013; 60: 1580–1588.CrossrefGoogle Scholar

  • [92]

    Yamazaki T, Froelicher VF, Myers J, Chun S, Wang P. Spatial QRS-T angle predicts cardiac death in a clinical population. Heart Rhythm 2005; 2: 73–78.CrossrefGoogle Scholar

  • [93]

    Yang H, Bukkapatnam ST, Komanduri R. Spatiotemporal representation of cardiac vectorcardiogram (VCG) signals. Biomed Eng Online 2012; 11: 1–15.CrossrefGoogle Scholar

  • [94]

    Yang Q, Kiyoshige K, Fujimoto T, et al. Vector u loop in patients with old myocardial infarction. Clin Cardiol 1989; 12: 277–282.CrossrefGoogle Scholar

  • [95]

    Zabel M, Malik M. Practical use of T wave morphology assessment. Cardiac Electrophysiol Rev 2002; 6: 316–322.Google Scholar

  • [96]

    Zabel M, Acar B, Klingenheben T, Franz MR, Hohnloser SH, Malik M. Analysis of 12-lead T-wave morphology for risk stratification after myocardial infarction. Circulation 2000; 102: 1252–1257.CrossrefGoogle Scholar

  • [97]

    Zabel M, Malik M, Hnatkova K, et al. Analysis of T-wave morphology from the 12-lead electrocardiogram for prediction of long-term prognosis in male US veterans. Circulation 2002; 105: 1066–1070.Google Scholar

  • [98]

    Zhang Z-m, Prineas RJ, Case D, Soliman EZ, Rautaharju PM. Comparison of the prognostic significance of the electrocardiographic QRS/T angles in predicting incident coronary heart disease and total mortality (from the atherosclerosis risk in communities study). Am J Cardiol 2007; 100: 844–849.CrossrefGoogle Scholar

About the article

Corresponding author: Muhammad A. Hasan, PhD, Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada, Phone: +1-416-979-5000, ext. 2048, E-mail: mahasan@ryerson.ca; muhammad.hasan@adelaide.edu.au Department of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA 5005, Australia; and Centre for Biomedical Engineering (CBME), The University of Adelaide, Adelaide, SA 5005, Australia


Received: 2014-11-08

Accepted: 2015-04-17

Published Online: 2015-05-20

Published in Print: 2016-02-01


Citation Information: Biomedical Engineering / Biomedizinische Technik, Volume 61, Issue 1, Pages 3–17, ISSN (Online) 1862-278X, ISSN (Print) 0013-5585, DOI: https://doi.org/10.1515/bmt-2015-0005.

Export Citation

©2016 by De Gruyter.Get Permission

Citing Articles

Here you can find all Crossref-listed publications in which this article is cited. If you would like to receive automatic email messages as soon as this article is cited in other publications, simply activate the “Citation Alert” on the top of this page.

[1]
Jens Haueisen and Tilmann Sander-Thömmes
Biomedical Engineering / Biomedizinische Technik, 2016, Volume 61, Number 1, Page 1
[2]
Sachin Nayyar, Muhammad A. Hasan, Kurt C. Roberts-Thomson, Thomas Sullivan, and Mathias Baumert
Cardiovascular Engineering and Technology, 2017, Volume 8, Number 2, Page 219

Comments (0)

Please log in or register to comment.
Log in