Effects of noise and filtering on SVD-based morphological parameters of the T wave in the ECG

Normal ranges and potential modifiers of T-wave morphology parameters among healthy individuals: A meta-analysis

BACKGROUND

T-wave morphology parameters, such as total cosine R-to-T (TCRT), T-wave loop dispersion (TWLD), T-wave morphology dispersion (TMD), and T-wave residuum (TWR), were suggested to be robust markers for adverse cardiovascular outcomes. Yet, the normal range of these parameters is unknown. This study aimed to evaluate the weighted normal values of T-wave morphology parameters of healthy individuals and study the effect of potential modifiers.

METHODS

A systematic search of studies published in PubMed was conducted. Only those reporting on control groups of healthy individuals were included. Weighted means were calculated for TCRT, TWLD, TMD, and TWR. Linear regression analysis was conducted for age, percentage of males, heart rate, and QTc.

RESULTS

The weighted TCRT was 0.40 ± 0.05, significantly higher than the various cutoffs previously suggested to identify high risk. There was some overlap between the results of weighted normal TMD (19.42 ± 6.77°), TWLD (38.51 ± 0.31), and relative TWR (0.118 ± 0.056%) and reports on the same parameters from patients with cardiovascular disease. Women were also characterized by higher TWLD, TMD, and relative TWR. TCRT was negatively correlated with age and heart rate, and positively correlated with QTc duration, although all associations were weak (R²  < 0.9).

CONCLUSIONS

T-wave morphology parameters reported in the medical literature span a broad range of values in healthy individuals. Seemingly abnormal values of TWLD, TMD, and relative TWR were often reported in healthy adults. The variability between studies may stem from methodological issues. Therefore, standardizing the methodology for measuring T-wave morphology is imperative.

Fault Model and Travelling Wave Matching Based Single Terminal Fault Location Algorithm for T-Connection Transmission Line: A Yunnan Power Grid Study

Due to the complex structure of the T-connection transmission lines, it is extremely difficult to identify the reflected travelling wave from the fault point and that from the connection point by the measurement from only one terminal. According to the characteristics of the structure of the T-connection transmission line, the reflection of the travelling wave within the line after the failure of different sections in T-connection transmission line are analyzed. Based on the lattice diagram of the travelling wave, the sequence of travelling waves detected at the measuring terminal varies with the fault distance and the faulty section. Moreover, the sequence of travelling waves detected in one terminal is unique at each faulty section. This article calculates the arrival time of travelling waves of fault points at different locations in different sections to form the collection of the travelling wave arrival time sequence. Then the sequence of travelling waves of the new added fault waveforms is extracted to compare with the sequences in the collection for the faulty section identification and fault location. This proposed method can accurately locate the fault with different fault types, fault resistances and system impedances by only single-terminal fault data. Both Power Systems Computer Aided Design/ Electromagnetic Transients including DC (PSCAD/EMTDC) and actual measurement data are implemented to verify the effectiveness of this method.

QRS-T morphology measured from exercise electrocardiogram as a predictor of cardiac mortality

AIMS

Total cosine R-to-T (TCRT) measured from the standard 12-lead electrocardiogram (ECG) reflects the spatial relationship between depolarization and repolarization wavefronts and a low TCRT value is a marker of poor prognosis. We tested the hypothesis that measurement of TCRT or QRS/T angle from exercise ECG would provide even more powerful prognostic information.

METHODS AND RESULTS

The prognostic significances of TCRT and QRS/T angle were assessed from exercise ECG recordings in 1297 patients [age 56 ± 13 years (mean ± SD), 67% males] undergoing a clinically indicated bicycle stress-test and the subsequent follow-up. During an average follow-up of 45 ± 12 months, 74 patients died (5.7%); 34 (2.6%) were cardiac deaths, and 24 (1.9%) were sudden cardiac deaths. Total cosine R-to-T and QRS/T angle exhibited a correlation with the RR intervals in the total cohort, but the individual responses were variable, e.g. median correlation of TCRT-RR was 0.89 with an inter-quartile range from 0.55 to 0.98. A reduced correlation of TCRT-RR during the recovery phase of exercise ECG predicted cardiac death [adjusted heart rate (HR) 3.5, 95% confidence interval (CI): 1.8-6.8, P= 0.001] similarly as the baseline TCRT measured from ECG at rest (adjusted HR 3.4, 95% CI: 1.4-8.1, P= 0.01). The poor correlation between the TCRT-RR both during the exercise and recovery was specifically related to a risk of sudden cardiac death (adjusted HR 6.2, 95% CI: 2.1-17.8, P< 0.001).

CONCLUSIONS

Loss of rate-adaptation of the spatial relationship between depolarization and repolarization wavefronts is a strong predictor of cardiac death, especially of sudden cardiac death.

Dynamics and rate-dependence of the spatial angle between ventricular depolarization and repolarization wave fronts during exercise ECG

BACKGROUND

QRS/T angle and the cosine of the angle between QRS and T-wave vectors (TCRT), measured from standard 12-lead electrocardiogram (ECG), have been used in risk stratification of patients. This study assessed the possible rate dependence of these variables during exercise ECG in healthy subjects.

METHODS

Forty healthy volunteers, 20 men and 20 women, aged 34.6 +/- 3.4, underwent an exercise ECG testing. Twelve-lead ECG was recorded from each test subject and the spatial QRS/T angle and TCRT were automatically analyzed in a beat-to-beat manner with custom-made software. The individual TCRT/RR and QRST/RR patterns were fitted with seven different regression models, including a linear model and six nonlinear models.

RESULTS

TCRT and QRS/T angle showed a significant rate dependence, with decreased values at higher heart rates (HR). In individual subjects, the second-degree polynomic model was the best regression model for TCRT/RR and QRST/RR slopes. It provided the best fit for both exercise and recovery. The overall TCRT/RR and QRST/RR slopes were similar between men and women during exercise and recovery. However, women had predominantly higher TCRT and QRS/T values. With respect to time, the dynamics of TCRT differed significantly between men and women; with a steeper exercise slope in women (women, -0.04/min vs -0.02/min in men, P < 0.0001). In addition, evident hysteresis was observed in the TCRT/RR slopes; with higher TCRT values during exercise.

CONCLUSIONS

The individual patterns of TCRT and QRS/T angle are affected by HR and gender. Delayed rate adaptation creates hysteresis in the TCRT/RR slopes.

New Vectorcardiographic non-planarity measure of T-wave loop improves separation between healthy subjects and myocardial infarction patients

Principal component analysis of vectorcardio-graphic T-wave loop has been shown to be a potential tool to describe the abnormality of the cardiac repolarization and to predict cardiac events in patients with cardiac disease. In this paper a new method for estimating the non-planarity of the T-wave loop is introduced and tested with healthy subjects and subjects with anterior or inferior myocardial infarction. The method is based on the resamping of T-wave data points with respect to the arc-length, the total least squares plane fitting, the identifying and reordering of the fitted axes, and decomposing the optimal rotation matrix. A recently published related measure, PCA3, was used for comparison purposes. The results showed that the non-planarity of T-wave loop increased significantly in patients with myocardial infarction compared to the healthy group. The new method separated healthy and patient groups with p-value 0.002 while PCA3 only with p-value 0.075. The new method was superior to PCA3 in separating the healthy patients from both infarction types.