A new approach for TU complex characterization

Circulation Journal, 2006

ors et al assessed the orientation of the Taxis for cardiac risk stratification based on the theory of diagnostic vectorcardiography. 1 The Taxis was a strong and independent predictor of fatal and non-fatal cardiac events in the population of the Rotterdam study. Furthermore, the prognostic value of an abnormal Taxis has been proved to be greater than other electrocardiogram (ECG) risk factors of T-wave inversion and ST depression. However, the physiologic meaning of an abnormal Taxis remains unclear. Recently, T-wave morphology analysis (TMA) was hypothesized to quantify the irregularities of ventricular repolarization based on singular value decomposition of standard 12-lead ECGs. 2 TMA analysis assesses both ventricular depolarization and repolarization independent of the accuracy of measuring the repolarization process, such as QT interval and QT dispersion. Thus, TMA makes important the relationship between the QRS and T-wave vectors, and the morphological varieties of the T-wave. The total cosine R-toT (TCRT) in the TMA descriptors is dependent on the spatial angle between depolarization and repolarization, in keeping with the concept of the ventricular gradient (VG). Zabel et al reported that the TCRT is the only descriptor of TMA that is a strong and independent predictor of adverse outcome in patients with myocardial infarction (MI). 3 Both the Taxis and TCRT are derived from the computed analysis of a vectrocardiographic ECG reconstructed from the standard 12-lead ECG. 1,2 A TCRT less than-0.888 is associated with increased 5-year cardiac mortality in a population with MI. 4 Furthermore, a TCRT less than-0.888 occurs in the case of a vectorcardiographic ECG with an angle >150 degrees between the QRS loop and the T-wave loop. Thus, we propose a new indicator relating the axes of QRS and T-waves on the surface ECG. In this study, we evaluated its characteristics in patients with cardiomyopathy (CM) or MI, which often present with T-wave inversions and ST depression. The aim of this study was to assess the correlation between TCRT and the axes of QRS and T-wave on the surface ECG in patients with these conditions.

Journal of Electrocardiology, 1999

There is growing evidence that beat-to-beat changes in ventricular repolarization contribute to increased vulnerability to ventricular arrhythmias. Beat-to-beat repolarization variability is usually measured in the electrocardiogram (ECG) by tracking consecutive QT or RT intervals. However, these measurements strongly depend on the accurate identification of T-wave endpoints, and they do not reflect changes in repolarization morphology. In this article, we propose a new computerized time-domain method to measure beat-to-beat variability of repolarization morphology without the need to identify T-wave endpoints. The repolarization correlation index (RCI) is computed for each beat to determine the difference between the morphology of repolarization within a heart-rate dependent repolarization window compared to a template (median) repolarization morphology. The repolarization variability index (RVI) describes the mean value of repolarization correlation in a studied ECG recording. To validate our method, we analyzed repolarization variability in 128-beat segments from Holter ECG recordings of 42 ischemic cardiomyopathy (ICM) patients compared to 36 healthy subjects. The ICM patients had significantly higher values of RVI than healthy subjects (in lead X: 0.045 -+ 0.035 vs. 0.024 _+ 0.010, respectively; P < .001); 18 (43%) ICM patients had RVI values above the 97.5th percentile of healthy subjects (>0.044). No significant correlation was found between the RVI values and the magnitude of heart rate, heart rate variability, QTc interval duration, or ejection fraction in studied ICM patients. In conclusion, our time-domain method, based on computation of repolarization correlation indices for consecutive beats, provides a new approach to quantify beat-to-beat variability of repolarization morphology without the need to identify T-wave endpoints.

Circulation, 1989

Quantification of the electrocardiographic ventricular repolarization involving the T-U wave complex is usually performed with reference to the axis of the T wave and the QT interval duration. A novel quantitative approach to improve the description of ventricular repolarization was applied to the digitized electrocardiograms of 423 normal subjects. Six electrocardiographic repolarization characteristics were identified: duration, rate, area, symmetry, late phenomena, and interlead heterogeneity. A computer algorithm was designed to automatically interpret the electrocardiographic repolarization segment and measure 11 variables that quantified these repolarization characteristics. The application of redundancy-reduction techniques selected a final set of seven variables that were used in the statistical analysis. The QT interval, which was included in the initial group of variables, was replaced by the time interval between S wave offset and T wave maximum. All selected electrocardi...

Annals of the New York Academy of Sciences, 1990

2001

Elevated ventricular repolarization lability is believed to be linked to the risk of ventricular tachycardia/ ventricular fibrillation. However, ventricular repolariza-tion is a complex electrical phenomenon, and abnormalities in ventricular repolarization are not completely understood. To evaluate repolarization lability, vector-cardiography (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 labil-ity, which may have potential utility for further study.

International Journal of Engineering Research and Technology (IJERT), 2016

https://www.ijert.org/detection-of-ventricular-tachycardia-paced-rhythm-and-idioventricular-rhythm-through-qrs-complex-analysis https://www.ijert.org/research/detection-of-ventricular-tachycardia-paced-rhythm-and-idioventricular-rhythm-through-qrs-complex-analysis-IJERTV5IS040633.pdf ECG signal plays a necessary part in the perception and study of heart diseases. Detection and monitoring of RR interval and QRS complex is a vital method in the analysis of ECG patterns to diagnose abnormal behavior of the heart. Abnormalities in the patterns are used to detect arrhythmia arising out of atypical electrical flow in the functioning of the heart. The rate and rhythm of these patterns render information that can be correlated with normal values to detect and categorize conditions of arrhythmia. While theoretical models exist for extraction of arrhythmia information from ECG, real-time analysis and detection have remained a challenge. An algorithm based on the Pan-Tompkins method is used to detect R peaks, from which we can measure heart rate using average R-R interval, was used. Detection of QRS duration, which is also a factor to identify the different types of arrhythmia. As a further step, uncertainity in the QRS duration and uncertainity in position of peaks helps to eliminate AWGN noise reducing false detections. The algorithm is implemented considering both arrhythmia screening and real-time monitoring applications. For validation of the algorithm, data from different internationally published databases like to MIT-BIH, with known arrhythmia conditions like Ventricular Tachycardia, Paced rhythm and Idioventricular rhythm and PTB, ESTST samples with known number of peaks have been used as reference signals and corresponding published results are compared with expected outcomes.

2001

Ventricular repolarisation abnormalities are important in arrhythmia provocation. The dispersion of repolarisation duration is not the only aspect of repolarisation heterogeneity. Spatial vectorcardiographic descriptors constitute a novel approach to quantify ventricular repolarisation. To test the ability of vectorcardiographic descriptors to discriminate between hypertensives with high or low blood pressure (BP), 110 treated hypertensives (mean age 63.6 ؎ 12.1 years) were classified in the high (systolic BP у160 mm Hg or diastolic BP у95 mm Hg) (n ‫؍‬ 67), or the low (systolic BP Ͻ 160 mm Hg and diastolic BP Ͻ95 mm Hg) (n ‫؍‬ 43) BP group. The maximum QT, JT, and T peak-T end intervals and the QT, JT, and T peak-T end dispersion were calculated from a digitally recorded 12-lead electrocardiogram (ECG). X, Y, and Z leads were reconstructed from the 12-lead ECG. The amplitude of the maximum spatial T

Computers &amp; Electrical Engineering, 2014

A simple and efficient new method for QRS detection in Electrocardiogram (ECG) is proposed in this paper. Initially data is preprocessed using two stage median filter for removing baseline drift. The second stage enhances the peaks of ECG wave components by using sixth power of signal. The next stage identifies the QRS complex by taking a variable window size. The detection sensitivity (Se) and positive predictivity (+P) of CSE (Common Standards for Quantitative Electrocardiography) measurement database, MIT/BIH (Massachusetts Institute of Technology/Beth Israel Hospital) Arrhythmia database, European ST-T database and QT database are Se 99.51 & +P 99.69%, Se 99.21 & +P 99.34%, Se 99.53 & +P 99.72% and Se 99.87 & +P 99.95% respectively. These four standard databases used to perform QRS detection considered 368 cases, tested 1,006,168 beats and achieved overall average sensitivity 99.52% and positive predictivity 99.69%. The MIT/BIH Noise Stress Test Database also tested by proposed method.

2019

PyECG is a software tool for QT interval analysis in the electrocardiogram (ECG). The software is written in Python 3.6 and among its main features includes signal filtering, Q onset, R peak and T offset detection algorithms, classifiers for irregular heartbeat identification and rejection, and tools for easy correction of automatically generated annotations. Moreover, the software includes a signal quality assessment module in order to help the researcher deciding which lead should be used. The software tool computes and plots the QT Variability Index (QTVI) and QT dynamicity parameters. Since the software is designed for cardiologists and specialists with no or little programming skills, the graphical user interface is intuitive, compact and easy to use.

Annals of Noninvasive Electrocardiology, 2000

Background: QT interval dispersion (QTd) measured from the surface ECG has emerged as the most common noninvasive method for assessing heterogeneity of ventricular repolarization. Although QTd correlates with dispersion of monophasic action potential duration at 90% repolarization and with dispersion of recovery time recorded from the epicardium, total T-wave area, representing a summation of vectors during this time interval, has been shown to have the highest correlation with these invasive measures of dispersion of repolarization. However, recent clinical studies suggest that the ratio of the second to first eigenvalues of the spatial T-wave vector using principal component analysis (PCA ratio) may more accurately reflect heterogeneity of ventricular repolarization. Methods: To better characterize the ECG correlates of surface ECG measures of heterogeneity of ventricular repolarization and to establish normal values of these criteria using an automated measurement method, the relations of QRS onset to T-wave offset (QT,d) and to T-wave peak (QT,d) dispersion and the PCA ratio to T-wave area and amplitude, heart rate, QRS axis and duration, and the QT, interval were examined in 163 asymptomatic subjects with normal resting ECGs and normal left ventricular mass and function. QT, d and QT, d were measured by computer from digitized ECGs as the difference between the maximum and minimum QT, and QT, intervals, respectively. Results: In univariate analyses, a significant correlation was found between the sum of the T-wave area and the PCA ratio (R =-0.46, P < O.OOl), but there was no significant correlation of the sum of T-wave area with QT, d (R = 0.1 1, P = NS) or QT, d (R=0.09, P = NS). There were only modest correlations between QT, d and QT, d (R = 0.45) and between the PCA ratio and QT, d (R = 0.29) and QT, d (R = 0.49) (each P < 0.001). In stepwise multivariate linear regression analyses, the PCA ratio was significantly related to the sum of T-wave area, T-wave amplitude in aVL, and to female gender (overall R = 0.54, P < 0.001 1, QT, d correlated only with the maximum QT, interval (R = 0.39, P < 0.001), and QT, d was related to heart rate and QRS axis (overall R = 0.36, P < 0.001). In addition, the normal interlead dispersion of repolarization as measured by QT, d was significantly greater than dispersion measured by QT, d (23.5 ? 11.5 ms vs 18.3 2 11.2 ms, P < 0.001). Conclusions: These findings provide new information on ECG measures of heterogeneity of repolarization in normal subjects, with a significantly higher intrinsic variability of Q to T-peak than Q to T-offset dispersion and only modest correlation between these two measures. The independent relation of the PCA ratio to the sum of T-wave area suggests that the PCA ratio may be a more accurate surface ECG computers; electrocardiography; electrophysiology; intervals; QT dispersion reflection of the heterogeneity of ventricular repolarization.

2013

The American Journal of Cardiology, 2002

I ncreased heterogeneity of ventricular repolarization favors the development of serious ventricular arrhythmias. One way to assess increased dispersion of repolarization is the measurement of QT dispersion.

2003

This paper presents a novel algorithm to detect onset and duration of QRS complexes. After low-pass filtering, the ECG signal is converted to a curve length signal by a transform in which a nonlinear scaling factor is introduced to enhance the QRS complex and to suppress unwanted noise. Adoptive thresholds are applied to the length signal to determine the onset and duration of the QRS complex. The algorithm was evaluated with the complete set of single channel ECGs (signal 0) from the MIT-BIH Arrhythmia Database, and achieved a gross QRS sensitivity of 99.65% and a gross QRS positive predictive accuracy of 99.77%. The QRS onsef determination is very stable and is insensitive to QRS morphology change. The noise tolerance of the algorithm was evaluated using the MIT-BIH Noise Stress Test Database. The C source code for the single-channel algorithm has been contributed to PhysioToolkit and is freely available from PhysioNet (www.physionet.org).

IEEE Transactions on Biomedical Engineering, 2011

Temporal heterogeneity of ventricular repolarization is a key quantity for the development of ventricular reentrant arrhythmia. The paper introduces the V-index, a novel electrocardiogram (ECG)-based estimator of the standard deviation of ventricular myocytes' repolarization times s ϑ. Differently from other ECG metrics of repolarization heterogeneity, the V-index was derived from the analysis of a biophysical model of the ECG, where repolarization is described by the Dominant T-wave (DTW) paradigm. The model explains the shape of T waves in each lead as a projection of a main waveform (the DTW) and its derivatives weighted by scalars, the lead factors. A mathematical formula is derived to link the heterogeneity of ventricular repolarization s ϑ and the V-index. The formula was verified using synthetic 12-Leads ECGs, generated with a direct electrophysiological model for increasing values of s ϑ (in the range 20 to 70 ms). A linear relationship between the V-index and s ϑ was observed, V ≈ 0.675 s ϑ + 1.8 ms (R 2 = 0.9992). Finally, 68 ECGs from the E-OTH-12-0068-010 database of the Telemetric and Holter ECG Warehouse (THEW) were analyzed. The V-index coherently increased after sotalol administration, a drug know to have QT-prolonging potential (p 0.001).