SVD-based on-line exercise ECG signal orthogonalization

Intra-subject stability of different expressions of spatial QRS-T angle and their relationship to heart rate

Three-dimensional angle between the QRS complex and T wave vectors is a known powerful cardiovascular risk predictor. Nevertheless, several physiological properties of the angle are unknown or poorly understood. These include, among others, intra-subject profiles and stability of the angle relationship to heart rate, characteristics of angle/heart-rate hysteresis, and the changes of these characteristics with different modes of QRS-T angle calculation. These characteristics were investigated in long-term 12-lead Holter recordings of 523 healthy volunteers (259 females). Three different algorithmic methods for the angle computation were based on maximal vector magnitude of QRS and T wave loops, areas under the QRS complex and T wave curvatures in orthogonal leads, and weighted integration of all QRS and T wave vectors moving around the respective 3-dimensional loops. These methods were applied to orthogonal leads derived either by a uniform conversion matrix or by singular value decomposition (SVD) of the original 12-lead ECG, giving 6 possible ways of expressing the angle. Heart rate hysteresis was assessed using the exponential decay models. All these methods were used to measure the angle in 659,313 representative waveforms of individual 10-s ECG samples and in 7,350,733 individual beats contained in the same 10-s samples. With all measurement methods, the measured angles fitted second-degree polynomial regressions to the underlying heart rate. Independent of the measurement method, the angles were found significantly narrower in females (p < 0.00001) with the differences to males between 10o and 20o, suggesting that in future risk-assessment studies, different angle dichotomies are needed for both sexes. The integrative method combined with SVD leads showed the highest intra-subject reproducibility (p < 0.00001). No reproducible delay between heart rate changes and QRS-T angle changes was found. This was interpreted as a suggestion that the measurement of QRS-T angle might offer direct assessment of cardiac autonomic responsiveness at the ventricular level.

Deep-Learning-Based Estimation of the Spatial QRS-T Angle from Reduced-Lead ECGs

The spatial QRS-T angle is a promising health indicator for risk stratification of sudden cardiac death (SCD). Thus far, the angle is estimated solely from 12-lead electrocardiogram (ECG) systems uncomfortable for ambulatory monitoring. Methods to estimate QRS-T angles from reduced-lead ECGs registered with consumer healthcare devices would, therefore, facilitate ambulatory monitoring. (1) Objective: Develop a method to estimate spatial QRS-T angles from reduced-lead ECGs. (2) Approach: We designed a deep learning model to locate the QRS and T wave vectors necessary for computing the QRS-T angle. We implemented an original loss function to guide the model in the 3D space to search for each vector's coordinates. A gradual reduction of ECG leads from the largest publicly available dataset of clinical 12-lead ECG recordings (PTB-XL) is used for training and validation. (3) Results: The spatial QRS-T angle can be estimated from leads {I, II, aVF, V2} with sufficient accuracy (absolute mean and median errors of 11.4° and 7.3°) for detecting abnormal angles without sacrificing patient comfortability. (4) Significance: Our model could enable ambulatory monitoring of spatial QRS-T angles using patch- or textile-based ECG devices. Populations at risk of SCD, like chronic cardiac and kidney disease patients, might benefit from this technology.

Review of Processing Pathological Vectorcardiographic Records for the Detection of Heart Disease

Vectorcardiography (VCG) is another useful method that provides us with useful spatial information about the electrical activity of the heart. The use of vectorcardiography in clinical practice is not common nowadays, mainly due to the well-established 12-lead ECG system. However, VCG leads can be derived from standard 12-lead ECG systems using mathematical transformations. These derived or directly measured VCG records have proven to be a useful tool for diagnosing various heart diseases such as myocardial infarction, ventricular hypertrophy, myocardial scars, long QT syndrome, etc., where standard ECG does not achieve reliable accuracy within automated detection. With the development of computer technology in recent years, vectorcardiography is beginning to come to the forefront again. In this review we highlight the analysis of VCG records within the extraction of functional parameters for the detection of heart disease. We focus on methods of processing VCG functionalities and their use in given pathologies. Improving or combining current or developing new advanced signal processing methods can contribute to better and earlier detection of heart disease. We also focus on the most commonly used methods to derive a VCG from 12-lead ECG.

Spatial distribution of physiologic 12-lead QRS complex

The normal physiologic range of QRS complex duration spans between 80 and 125 ms with known differences between females and males which cannot be explained by the anatomical variations of heart sizes. To investigate the reasons for the sex differences as well as for the wide range of normal values, a technology is proposed based on the singular value decomposition and on the separation of different orthogonal components of the QRS complex. This allows classification of the proportions of different components representing the 3-dimensional representation of the electrocardiographic signal as well as classification of components that go beyond the 3-dimensional representation and that correspond to the degree of intricate convolutions of the depolarisation sequence. The technology was applied to 382,019 individual 10-s ECG samples recorded in 639 healthy subjects (311 females and 328 males) aged 33.8 ± 9.4 years. The analyses showed that QRS duration was mainly influenced by the proportions of the first two orthogonal components of the QRS complex. The first component demonstrated statistically significantly larger proportion of the total QRS power (expressed by the absolute area of the complex in all independent ECG leads) in females than in males (64.2 ± 11.6% vs 59.7 ± 11.9%, p < 0.00001—measured at resting heart rate of 60 beats per minute) while the second component demonstrated larger proportion of the QRS power in males compared to females (33.1 ± 11.9% vs 29.6 ± 11.4%, p < 0.001). The analysis also showed that the components attributable to localised depolarisation sequence abnormalities were significantly larger in males compared to females (2.85 ± 1.08% vs 2.42 ± 0.87%, p < 0.00001). In addition to the demonstration of the technology, the study concludes that the detailed convolution of the depolarisation waveform is individual, and that smoother and less intricate depolarisation propagation is the mechanism likely responsible for shorter QRS duration in females.

Heart Rate Dependency and Inter-Lead Variability of the T Peak - T End Intervals

The electrocardiographic (ECG) assessment of the T peak–T end (Tpe) intervals has been used in many clinical studies, but several related physiological aspects have not been reported. Specifically, the sources of the Tpe differences between different ECG leads have not been systematically researched, the relationship of Tpe duration to underlying heart rate has not been firmly established, and little is known about the mutual correspondence of Tpe intervals measured in different ECG leads. This study evaluated 796,620 10-s 12-lead ECGs obtained from long-term Holters recorded in 639 healthy subjects (311 female) aged 33.8 ± 9.4 years. For each ECG, transformation to orthogonal XYZ lead was used to measure Tpe in the orthogonal vector magnitude (used as a reference for lead-to-lead comparisons) and to construct a three-dimensional T wave loop. The loop roundness was expressed by a ratio between its circumference and length. These ratios were significantly related to the standard deviation of Tpe durations in different ECG leads. At the underlying heart rate of 60 beats per minute, Tpe intervals were shorter in female than in male individuals (82.5 ± 5.6 vs 90.0 ± 6.5 ms, p < 0.0001). When studying linear slopes between Tpe intervals measured in different leads and the underlying heart rate, we found only minimal heart rate dependency, which was not systematic across the ECG leads and/or across the population. For any ECG lead, positive Tpe/RR slope was found in some subjects (e.g., 79 and 25% of subjects for V2 and V4 measurements, respectively) and a negative Tpe/RR slope in other subjects (e.g., 40 and 65% for V6 and V5, respectively). The steepest positive and negative Tpe/RR slopes were found for measurements in lead V2 and V4, respectively. In all leads, the Tpe/RR slope values were close to zero, indicating, on average, Tpe changes well below 2 ms for RR interval changes of 100 ms. On average, longest Tpe intervals were measured in lead V2, the shortest in lead III. The study concludes that the Tpe intervals measured in different leads cannot be combined. Irrespective of the measured ECG lead, the Tpe interval is not systematically heart rate dependent, and no heart rate correction should be used in clinical Tpe investigations.

CEEMDAN-IMFx-PCA-CICA: an improved single-channel blind source separation in multimedia environment for motion artifact reduction in ambulatory ECG

Long-term monitoring of ECG via wearable monitoring systems has already been widely adopted to detect and prevent heart diseases. However, one of the main issues faced by wearable ECG monitoring systems is that motion artifacts significantly affect the systems' stability and reliability. Therefore, motion artifact reduction is a very challenging task in filtering and processing physiological signals. Based on the existing algorithms and ECG prior knowledge, in this paper, we propose an algorithm, CEEMDAN-IMFx-PCA-CICA, for motion artifact reduction in ambulatory ECG signals using single-channel blind source separation technique. Our algorithm first utilizes CEEMDAN to decompose the mixed signals into IMFs (intrinsic mode function) containing different source signal features, thereby forming new multi-dimensional signals. Using the correlation between IMFx (IMF component with the most ECG features) and each IMF, and PCA are then applied to reduce the dimension of each IMF. Finally, the blind separation of the source ECG signals is achieved by using CICA with IMFx as the constraint reference component. The results of our experiments indicate that our algorithm outperformed CEEMDAN-CICA, CEEMDAN-PCA-CICA, and improved CEEMDAN-PCA-CICA. Besides, the number of iterations of the CICA is significantly reduced; the separated source signal is better; the obtained result is stable. Furthermore, the separated ECG signal has a higher correlation with the source ECG signal and a lower RRMSE, especially in the case of high noise-to-signal ratios.

Detection of T Wave Peak for Serial Comparisons of JTp Interval

Electrocardiogram (ECG) studies of drug-induced prolongation of the interval between the J point and the peak of the T wave (JTp interval) distinguished QT prolonging drugs that predominantly block the delayed potassium rectifier current from those affecting multiple cardiac repolarisation ion channel currents. Since the peak of the T wave depends on ECG lead, a “global” T peak requires to combine ECG leads into one-dimensional signal in which the T wave peak can be measured. This study aimed at finding the optimum one-dimensional representation of 12-lead ECGs for the most stable JTp measurements. Seven different one-dimensional representations were investigated including the vector magnitude of the orthogonal XYZ transformation, root mean square of all 12 ECG leads, and the vector magnitude of the 3 dominant orthogonal leads derived by singular value decomposition. All representations were applied to the median waveforms of 660,657 separate 10-s 12-lead ECGs taken from repeated day-time Holter recordings in 523 healthy subjects aged 33.5 ± 8.4 years (254 women). The JTp measurements were compared with the QT intervals and with the intervals between the J point and the median point of the area under the T wave one-dimensional representation (JT50 intervals) by means of calculating the residuals of the subject-specific curvilinear regression models relating the measured interval to the hysteresis-corrected RR interval of the underlying heart rate. The residuals of the regression models (equal to the intra-subject standard deviations of individually heart rate corrected intervals) expressed intra-subject stability of interval measurements. For both the JTp intervals and the JT50 intervals, the curvilinear regression residuals of measurements derived from the orthogonal XYZ representation were marginally but statistically significantly lower compared to the other representations. Using the XYZ representation, the residuals of the QT/RR, JTp/RR and JT50/RR regressions were 5.6 ± 1.1 ms, 7.2 ± 2.2 ms, and 4.9 ± 1.2 ms, respectively (all statistically significantly different; p < 0.0001). The study concludes that the orthogonal XYZ ECG representation might be proposed for future investigations of JTp and JT50 intervals. If the ability of classifying QT prolonging drugs is further confirmed for the JT50 interval, it might be appropriate to replace the JTp interval since with JT50 it appears more stable.

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.

Cardiac arrhythmia beat classification using DOST and PSO tuned SVM

BACKGROUND AND OBJECTIVE

The increase in the number of deaths due to cardiovascular diseases (CVDs) has gained significant attention from the study of electrocardiogram (ECG) signals. These ECG signals are studied by the experienced cardiologist for accurate and proper diagnosis, but it becomes difficult and time-consuming for long-term recordings. Various signal processing techniques are studied to analyze the ECG signal, but they bear limitations due to the non-stationary behavior of ECG signals. Hence, this study aims to improve the classification accuracy rate and provide an automated diagnostic solution for the detection of cardiac arrhythmias.

METHODS

The proposed methodology consists of four stages, i.e. filtering, R-peak detection, feature extraction and classification stages. In this study, Wavelet based approach is used to filter the raw ECG signal, whereas Pan-Tompkins algorithm is used for detecting the R-peak inside the ECG signal. In the feature extraction stage, discrete orthogonal Stockwell transform (DOST) approach is presented for an efficient time-frequency representation (i.e. morphological descriptors) of a time domain signal and retains the absolute phase information to distinguish the various non-stationary behavior ECG signals. Moreover, these morphological descriptors are further reduced in lower dimensional space by using principal component analysis and combined with the dynamic features (i.e based on RR-interval of the ECG signals) of the input signal. This combination of two different kinds of descriptors represents each feature set of an input signal that is utilized for classification into subsequent categories by employing PSO tuned support vector machines (SVM).

RESULTS

The proposed methodology is validated on the baseline MIT-BIH arrhythmia database and evaluated under two assessment schemes, yielding an improved overall accuracy of 99.18% for sixteen classes in the category-based and 89.10% for five classes (mapped according to AAMI standard) in the patient-based assessment scheme respectively to the state-of-art diagnosis. The results reported are further compared to the existing methodologies in literature.

CONCLUSIONS

The proposed feature representation of cardiac signals based on symmetrical features along with PSO based optimization technique for the SVM classifier reported an improved classification accuracy in both the assessment schemes evaluated on the benchmark MIT-BIH arrhythmia database and hence can be utilized for automated computer-aided diagnosis of cardiac arrhythmia beats.

Information theoretic multiscale truncated SVD for multilead electrocardiogram

BACKGROUND AND OBJECTIVE

In this paper an information theory based multiscale singular value decomposition (SVD) is proposed for multilead electrocardiogram (ECG) signal processing. The shrinkage of singular values for different multivariate multiscale matrices at wavelet scales is based on information content. It aims to capture and preserve the information of clinically important local waves like P-waves, Q-waves, T-waves and QRS-complexes.

METHODS

The information is derived through clinically relevant multivariate multiscale entropy in SVD domain modifying Shannon's entropy. This optimizes the approximate ranks for matrices to capture the clinical components of ECG signals appearing at different scales. A newly introduced multivariate clinical distortion (MCD) metric is computed and compared with existing subjective and objective signal distortion measures. The proposed method is tested with records from CSE multilead measurement library and PTB diagnostic ECG database for various pathological cases.

RESULTS

It gives average percentage root mean square difference (PRD), average normalized root mean square error (NRMSE), average wavelet energy based diagnostic distortion measure (WEDD) values 5.8879%, 0.0059 and 1.0760% respectively for myocarditis pathology. The corresponding MCD value is 1.9429%. The highest average PRD and average WEDD values are 11.4053% and 5.5194% for cardiomyopathy with the corresponding MCD value 1.4003%.

CONCLUSIONS

Based on WEDD values and mean opinion scores (MOS), the quality group of all processed signals fall under excellent category.

A Baseline Wander Tracking System for Artifact Rejection in Long-Term Electrocardiography

Long-term electrocardiogram (ECG) signals might suffer from relevant baseline disturbances during physical activity. Motion artifacts in particular are more pronounced with dry surface or esophageal electrodes which are dedicated to prolonged ECG recording. In this paper we present a method called baseline wander tracking (BWT) that tracks and rejects strong baseline disturbances and avoids concurrent saturation of the analog front-end. The proposed algorithm shifts the baseline level of the ECG signal to the middle of the dynamic input range. Due to the fast offset shifts, that produce much steeper signal portions than the normal ECG waves, the true ECG signal can be reconstructed offline and filtered using computationally intensive algorithms. Based on Monte Carlo simulations we observed reconstruction errors mainly caused by the non-linearity inaccuracies of the DAC. However, the signal to error ratio of the BWT is higher compared to an analog front-end featuring a dynamic input ranges above 15 mV if a synthetic ECG signal was used. The BWT is additionally able to suppress (electrode) offset potentials without introducing long transients. Due to its structural simplicity, memory efficiency and the DC coupling capability, the BWT is dedicated to high integration required in long-term and low-power ECG recording systems.

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

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.

Graphics-processor-unit-based parallelization of optimized baseline wander filtering algorithms for long-term electrocardiography

Long-term electrocardiogram (ECG) often suffers from relevant noise. Baseline wander in particular is pronounced in ECG recordings using dry or esophageal electrodes, which are dedicated for prolonged registration. While analog high-pass filters introduce phase distortions, reliable offline filtering of the baseline wander implies a computational burden that has to be put in relation to the increase in signal-to-baseline ratio (SBR). Here, we present a graphics processor unit (GPU)-based parallelization method to speed up offline baseline wander filter algorithms, namely the wavelet, finite, and infinite impulse response, moving mean, and moving median filter. Individual filter parameters were optimized with respect to the SBR increase based on ECGs from the Physionet database superimposed to autoregressive modeled, real baseline wander. A Monte-Carlo simulation showed that for low input SBR the moving median filter outperforms any other method but negatively affects ECG wave detection. In contrast, the infinite impulse response filter is preferred in case of high input SBR. However, the parallelized wavelet filter is processed 500 and four times faster than these two algorithms on the GPU, respectively, and offers superior baseline wander suppression in low SBR situations. Using a signal segment of 64 mega samples that is filtered as entire unit, wavelet filtering of a seven-day high-resolution ECG is computed within less than 3 s. Taking the high filtering speed into account, the GPU wavelet filter is the most efficient method to remove baseline wander present in long-term ECGs, with which computational burden can be strongly reduced.

Beat-to-beat vectorcardiographic analysis of ventricular depolarization and repolarization in myocardial infarction

Objectives

Increased beat-to-beat variability in the QT interval has been associated with heart disease and mortality. The purpose of this study was to investigate the beat-to-beat spatial and temporal variations of ventricular depolarization and repolarization in vectorcardiogram (VCG) for characterising myocardial infarction (MI) patients.

Methods

Standard 12-lead ECGs of 84 MI patients (22 f, 63±12 yrs; 62 m, 56±10 yrs) and 69 healthy subjects (17 f, 42±18 yrs; 52 m, 40±13 yrs) were investigated. To extract the beat-to-beat QT intervals, a template-matching algorithm and the singular value decomposition method have been applied to synthesise the ECG data to VCG. Spatial and temporal variations in the QRS complex and T-wave loops were studied by investigating several descriptors (point-to-point distance variability, mean loop length, T-wave morphology dispersion, percentage of loop area, total cosine R-to-T).

Results

Point-to-point distance variability of QRS and T-loops (0.13±0.04 vs. 0.10±0.04, p< 0.0001 and 0.16±0.07 vs. 0.13±0.06, p< 0.05) were significantly larger in the MI group than in the control group. The average T-wave morphology dispersion was significantly higher in the MI group than in the control group (62°±8° vs. 38°±16°, p< 0.0001). Further, its beat-to-beat variability appeared significantly lower in the MI group than in the control group (12°±5° vs. 15°±6°, p< 0.005). Moreover, the average percentage of the T-loop area was found significantly lower in the MI group than the controls (46±17 vs. 55±15, p< 0.001). Finally, the average and beat-to-beat variability of total cosine R-to-T were not found statistically significant between both groups.

Conclusions

Beat-to-beat assessment of VCG parameters may have diagnostic attributes that might help in identifying MI patients.

Cross-database evaluation of a multilead heartbeat classifier

In this paper, we studied the improvement in heartbeat classification achieved by including information from multilead ECG recordings in a previously developed and validated classification model. This model includes features from the RR interval series and morphology descriptors for each lead calculated from the wavelet transform. The experiments were carried out in the INCART database, available in Physionet, and the generalization was corroborated in private and public databases. In all databases, the AAMI recommendations for class labeling and results presentation were followed. Different strategies to integrate the additional information available in the 12-leads were studied. The best performing strategy consisted in performing principal component analysis to the wavelet transform of the available ECG leads. The performance indices obtained for normal beats were sensitivity (S) 98%, positive predictive value (P(+)) 93%; for supraventricular beats, (S) 86%, (P(+)) 91%; and for ventricular beats (S) 90%, (P(+)) 90%. The generalization capability of the chosen strategy was confirmed by applying the classifier to other databases with different number of leads with comparable results. In conclusion, the performance of the reference two-lead classifier was improved by taking into account additional information from the 12-leads.

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.

The time course of new T-wave ECG descriptors following single- and double-dose administration of sotalol in healthy subjects

INTRODUCTION

The aim of the study was to assess the time course effect of IKr blockade on ECG biomarkers of ventricular repolarization and to evaluate the accuracy of a fully automatic approach for QT duration evaluation.

METHODS

Twelve-lead digital ECG Holter was recorded in 38 healthy subjects (27 males, mean age = 27.4 + or - 8.0 years) on baseline conditions (day 0) and after administration of 160 mg (day 1) and 320 mg (day 2) of d-l sotalol. For each 24-hour period and each subject, ECGs were extracted every 10 minutes during the 4-hour period following drug dosage. Ventricular repolarization was characterized using three biomarker categories: conventional ECG time intervals, principal component analysis (PCA) analysis on the T wave, and fully automatic biomarkers computed from a mathematical model of the T wave.

RESULTS

QT interval was significantly prolonged starting 1 hour 20 minutes after drug dosing with 160 mg and 1 hour 10 minutes after drug dosing with 320 mg. PCA ventricular repolarization parameters sotalol-induced changes were delayed (>3 hours). After sotalol dosing, the early phase of the T wave changed earlier than the late phase prolongation. Globally, the modeled surrogate QT paralleled manual QT changes. The duration of manual QT and automatic surrogate QT were strongly correlated (R(2) = 0.92, P < 0.001). The Bland and Altman plot revealed a nonstationary systematic bias (bias = 26.5 ms + or - 1.96*SD = 16 ms).

CONCLUSIONS

Changes in different ECG biomarkers of ventricular repolarization display different kinetics after administration of a potent potassium channel blocker. These differences need to be taken into account when designing ventricular repolarization ECG studies.

Cardiac signal extraction in patients with Implantable Cardioverter Defibrillators

According to the guidelines the indication for Implantable Cardioverter Defibrillator (ICD) implantation is based on the ejection fraction. However, only a fraction of patients with implanted ICD shows live threatening arrhythmic events followed by adequate shocks. For this reason, further research is needed to find a more sensitive risk stratificator for patients prone to ventricular tachycardia or fibrillation. Unfortunately, standard prospective studies are time consuming. An alternative approach is to perform retrospective studies on patients with already implanted ICDs. So far, an implanted ICD is an exclusion criterion for Magnetic Field Imaging (MFI) studies. To overcome this problem several Blind Source Separation (BSS) algorithms have been tested to find out whether it is possible to separate the disturbances from the cardiac signals, in spite of the extreme difference in amplitude. Not all the methods are able to separate cardiac signal and disturbances. Temporal Decorrelation source Separation (TDSEP) is found to be superior both from a separation and performing point of view. For the first time it is possible to extract cardiac signals from measurements disturbed by an ICD, offering the possibility for a QRS-fragmentation analysis in patients with already implanted ICDs.

A hybrid ECG compression algorithm based on singular value decomposition and discrete wavelet transform

Increasing use of computerized ECG processing systems requires effective electrocardiogram (ECG) data compression techniques which aim to enlarge storage capacity and improve data transmission over phone and internet lines. This paper presents a compression technique for ECG signals using the singular value decomposition (SVD) combined with discrete wavelet transform (DWT). The central idea is to transform the ECG signal to a rectangular matrix, compute the SVD, and then discard small singular values of the matrix. The resulting compressed matrix is wavelet transformed, thresholded and coded to increase the compression ratio. The number of singular values and the threshold level adopted are based on the percentage root mean square difference (PRD) and the compression ratio required. The technique has been tested on ECG signals obtained from MIT-BIH arrhythmia database. The results showed that data reduction with high signal fidelity can thus be achieved with average data compression ratio of 25.2:1 and average PRD of 3.14. Comparison between the obtained results and recently published results show that the proposed technique gives better performance.

Multilead analysis of T-wave alternans in the ECG using principal component analysis

T-wave alternans (TWA) is a cardiac phenomenon associated with the mechanisms leading to sudden cardiac death. Several methods exist to automatically detect and estimate TWA in the ECG on a single-lead basis, and their main drawback is their poor sensitivity to low-amplitude TWA. In this paper, we propose a multilead analysis scheme to improve the detection and estimation of TWA. It combines principal component analysis with a single-lead method based on the generalized likelihood ratio test. The proposed scheme is evaluated and compared to a single-lead scheme by means of a simulation study, in which different types of simulated and physiological noise are considered under realistic conditions. Simulation results show that the multilead scheme can detect TWA with an SNR 30 dB lower and allows the estimation of TWA with an SNR 25 dB lower than the single-lead scheme. The two analysis schemes are also applied to stress test ECG records. Results show that the multilead scheme provides a higher detection power and that TWA detections obtained with this scheme are significantly different in healthy volunteers and ischemic patients, whereas they are not with the single-lead scheme.

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

Singular value decomposition (SVD) based electrocardiogram (ECG) morphology analysis is a novel method in the assessment of subtle abnormalities in the T wave morphology of 12-lead ECG. As various types of noise contaminate the ECG signal and create a bias for the morphological analyses, this study was designed to estimate the effects of noise on the SVD method in an experimental setup. Ideal signals were generated by filtering real ECG signals several times with the Savitzky-Golay filter. Random and real noise samples were superimposed on the ideal signals. The noisy signals were filtered with a power line interference filter combined with the Savitzky-Golay or the wavelet filter. Results show that noise increased both the dipolar and non-dipolar components significantly unless filtering was applied. R-TWR (relative T wave residuum) and A-TWR (absolute T wave residuum) were four to eight times higher in noisy signals. The experiments with patient data demonstrated that certain types of noise may even lead to erroneous classification of patients. Filtering brings the median values closer to the correct ones and decreases significantly the variance of the values of parameters.

T-wave morphology parameters based on principal component analysis reproducibility and dependence on T-offset position

BACKGROUND

T-wave morphology parameters based on principal component analysis (PCA) are candidate to better understand the relation between QT prolongation and torsades de pointes. We aimed to assess the repeatability and to determine the influence of T-end position on PCA parameters.

METHODS

Digital ECGs recorded from 30 subjects were used to assess short term (5 minutes), circadian and long-term (28 days) repeatability of PCA parameters. The T-end cursor position was moved backward and forward (+/- 8 ms) from its optimal position. We calculated QRS-T angle, PCA ratio, and T-wave residuum (TWR).

RESULTS

At long-term evaluation, coefficients of variation were 11.3 +/- 9.9%, 11.7 +/- 7.1%, and 23.0 +/- 22.0% for the QRS-T angle, PCA ratio, TWR, respectively. After moving the T-end cursor, repeatability was 0.42 +/- 0.2%, 1.00 +/- 1.04%, 4.0 +/- 4.2% for the same PCA parameters.

CONCLUSIONS

T-wave morphology parameters based on PCA are reproducible with the exception of TWR and QRS-T angle. In addition, PCA is robust, showing only little dependence on T-end cursor position. These data should be taken into account for safety pharmacology trials.

Influence of paper electrocardiogram digitizing on T wave and QRS complex morphology parameters

BACKGROUND

Many morphological parameters of the electrocardiogram (ECG) can be calculated from a digital ECG and paper prints of ECG after digitizing. However, the digitizing process, including printing, scanning, ECG contour extraction, and alignment, can produce changes to the signals, reducing the reliability of some sensitive parameters of QRS complex and T wave.

METHODS

The influence of the digitizing process on the parameters of T wave and QRS complex morphology was studied by comparing systematically the values of the nine ECG morphology parameters, computed from the digital ECG and the corresponding paper ECG. The robustness of the parameters to the digitizing process and their discrimination ability between healthy subjects and postinfarction patients were investigated.

RESULTS

The standard T wave parameters and all selected dipolar loop-parameters retained their robustness and discrimination ability during the digitizing process of the paper ECGs. The non-dipolar parameters distorted strongly, especially those of the QRS complex. The T wave-based non-dipolar parameters retained their discrimination ability during the digitizing process.

CONCLUSIONS

The selected standard T wave parameters and the dipolar loop-parameters calculated from properly digitized ECG paper prints can be utilized in patient studies. Non-dipolar parameters distort strongly but T wave-based parameters retain discriminatory information.

Comparison between ventricular gradient and a new descriptor of the wavefront direction of ventricular activation and recovery

BACKGROUND

Total R T cosine (TCRT) is a new descriptor of repolarization heterogeneity that quantifies the deviation between the directions of ventricular depolarization and repolarization. It revives the old concept of ventricular gradient (VG).

HYPOTHESIS

Our goal was to examine whether TCRT and VG contain nonredundant information by comparing their reaction to autonomic tests, namely, postural changes and Valsalva maneuver.

METHODS

Digital 12-lead electrocardiograms were recorded in 16 patients with cardiovascular syndrome X (SX, chest pain, exercise-induced ST-depression, normal coronary arteries, 3 men, age 60 +/- 9 years) and 40 healthy volunteers (31 men, age 33 +/- 7 years) during postural changes and Valsalva maneuver. The angle (VGA) [degrees] and magnitude (VGM) [ms.mV] of VG in reconstructed XYZ leads and TCRT (average cosine of the angles between the QRS and T vectors in mathematically reconstructed three-dimensional space) were calculated.

RESULTS

(mean +/- standard of the mean): In healthy subjects, VGM and TCRT decreased, whereas VGA increased in the sitting and standing compared with supine position (TCRT: 0.61 +/- 0.05,0.47 +/- 0.06,0.29 +/- 0.08, supine, sitting, and standing, p < 0.05) and during phase II Valsalva (TCRT: 0.47 +/- 0.06 vs. 0.61 +/- 0.05, p < 0.01 in supine, 0.24 +/- 0.08 vs. 0.37 +/- 0.07, p < 0.01 in standing). In patients with SX, VGM decreased in the standing position, VGA did not change significantly, while TCRT decreased only in patients without T-wave abnormalities (n = 9) (TCRT in standing and supine: 0.55 +/- 0.09 vs. 0.68 +/- 0.08, p < 0.05). VG(M) increased during Valsalva in patients with SX. Total R T cosine correlated strongly with VGA (r = -0.84, p < 0.00001) and, unlike VGM, did not correlate with heart rate.

CONCLUSIONS

Ventricular gradient and TCRT contain nonredundant information. In healthy subjects, they react sensitively to autonomic provocation. In patients with SX, their reaction is attenuated, which suggests disturbance of the autonomic control of repolarization.

A single-lead ECG enhancement algorithm using a regularized data-driven filter

We presented a novel way of deriving a subspace filter for enhancing a noisy electrocardiogram (ECG) signal contaminated by electromyogram (EMG). The new subspace filter was based on a multiple cycle prediction (MCP) modeling of a single-lead ECG. The adoption of an MCP model resulted in a data matrix more suitable for separating noise and signal subspaces than the linear prediction (LP) model that is implicitly assumed in many existing subspace filters. Alignment of ECG cycles of different length is required for MCP modeling and was handled by a dynamic time warping (DTW) algorithm. A run-time procedure was designed for automatically determining the signal space dimension adaptively. To validate the new filter in a quantitative way, 12 clean realistic ECG segments with different degrees of heart rate variability generated using the ECGSyn program were mixed with different realizations of EMG noise in the MIT-BIH Noise Stress Test Database and locally acquired EMG at a typical 10-dB signal-to-noise ratio. The performance of the proposed method was compared to three existing ECG enhancement algorithms and achieved encouraging results. In addition, various ECG recordings from MIT-Arrythmia database were also mixed with EMG noise and subjected to the same four filters resulting in a qualitative comparison of them.

Recent advances in understanding sex differences in cardiac repolarization

A number of gender differences exist in the human electrocardiogram (ECG): the P-wave and P-R intervals are slightly longer in men than in women, whilst women have higher resting heart rates than do men, but a longer rate-corrected QT (QT(C)) interval. Women with the LQT1 and LQT2 variants of congenital long-QT syndrome (LQTS) are at greater risk of adverse cardiac events. Similarly, many drugs associated with acquired LQTS have a greater risk of inducing torsades de pointes (TdP) arrhythmia in women than in men. There are also male:female differences in Brugada syndrome, early repolarisation syndrome and sudden cardiac death. The differences in the ECG between men and women, and in particular those relating to the QT interval, have been explored experimentally and provide evidence of differences in the processes underlying ventricular repolarization. The data available from rabbit, canine, rat, mouse and guinea pig models are reviewed and highlight involvement of male:female differences in Ca and K currents, although the possible involvement of rapid and persistent Na current and Na-Ca exchange currents cannot yet be excluded. The mechanisms underlying observed differences remain to be elucidated fully, but are likely to involve the influence of gonadal steroids. With respect to the QT interval and risk of TdP, a range of evidence implicates a protective role of testosterone in male hearts, possibly by both genomic and non-genomic pathways. Evidence regarding oestrogen and progesterone is less unequivocal, although the interplay between these two hormones may influence both repolarization and pro-arrhythmic risk.

Ventricular gradient as a risk factor in survivors of acute myocardial infarction

The total cosine between R and T (TCRT) (angular difference between the spatial QRS and T wave loops) is a technical elaboration of the concept of ventricular gradient (VG), whose power as a risk stratifier in post-MI patients has already been demonstrated. Recently, it was reported that TCRT differed significantly between healthy men and women, which suggested that its predictive power might be gender dependent. The aim of the study was to investigate TCRT and its association with cardiac mortality in male and female survivors of acute MI. TCRT was measured from digital Frank orthogonal XYZ-lead ECGs recorded before hospital discharge in 681 survivors of acute MI (82% men, age: men 57.0 +/- 8.4 years, women 59.6 +/- 8.1 years, P = 0.002). During a follow-up censored at 5 years, cardiac mortality rates were 9.7% and 12.1% in men and women, respectively (P = 0.42). There were no significant difference in TCRT between men and women (-0.150 +/- 0.704 vs -0.070 +/- 0.731, P = 0.26). In univariate Cox regression analysis, TCRT < -0.88 was related to a 5-year cardiac mortality in men (relative risk [RR] 3.67, 95% confidence interval [CI] 2.13-6.34, P = 1.9 x 10(-6)), and women (RR 5.16, 95% CI 1.83-14.56, P = 0.0015). Depressed TCRT was strongly associated with increased long-term cardiac mortality in survivors of acute MI. Its predictive power did not differ significantly between the sexes. The role of TCRT as a risk-stratifier in post-MI patients deserves further prospective assessment in multivariate models with established risk factors.

ECG data compression using truncated singular value decomposition

The method of truncated singular value decomposition (SVD) is proposed for electrocardiogram (ECG) data compression. The signal decomposition capability of SVD is exploited to extract the significant feature components of the ECG by decomposing the ECG into a set of basic patterns with associated scaling factors. The signal informations are mostly concentrated within a certain number of singular values with related singular vectors due to the strong interbeat correlation among ECG cycles. Therefore, only the relevant parts of the singular triplets need to be retained as the compressed data for retrieving the original signals. The insignificant overhead can be truncated to eliminate the redundancy of ECG data compression. The Massachusetts Institute of Technology-Beth Israel Hospital arrhythmia database was applied to evaluate the compression performance and recoverability in the retrieved ECG signals. The approximate achievement was presented with an average data rate of 143.2 b/s with a relatively low reconstructed error. These results showed that truncated SVD method can provide an efficient coding with high-compression ratios. The computational efficiency of the SVD method in comparing with other techniques demonstrated the method as an effective technique for ECG data storage or signals transmission. Index Terms-Data compression, electrocardiogram, feature extraction, quasi-periodic signal, singular value decomposition.

Suppression of electromyogram interference on the electrocardiogram by transform domain denoising

A method for suppression of electromyogram (EMG) interference in electrocardiogram (ECG) recordings is presented. By assuming that the EMG is long-term non-stationary Gaussian noise, two successive decompositions were proposed, and the data transformed for Wiener filtering. Successive ECG cycles were rearranged and aligned by the R-wave, forming a matrix containing separated heart cycles in its rows. A short-window discrete cosine transform (DCT) was applied to the columns of the matrix for inter-cycle de-correlation. Next, Wiener filtering in a translation-invariant wavelet domain was performed on the DCT-transformed matrix rows for de-correlation of the data into each ECG cycle. The method resulted in an improvement in the signal-to-noise ratio of more than 10 dB, a threefold reduction in mean relative amplitude errors and reduced ripple artifacts around the signal transients, thus preserving the waveform in diagnostically important signal segments.

Design of a wavelet interpolation filter for enhancement of the ST-segment

A wavelet interpolation filter (WIF) is designed for the removal of motion artifacts in the ST-segment of stress ECGs. The WIF consists of two parts. One part is a wavelet transform that decomposes the stress ECG signal into several frequency bands using a Haar wavelet. The other part is an interpolation method, such as the spline technique, that is used to enhance the reconstruction performance of the signal decomposed by the wavelet transform. To evaluate the performance of the WIF, three indices are used: signal-to-noise ratio (SNR), reconstruction square error (RSE) and standard deviation (SD). The MIT/BIH arrhythmia database, the European ST-T database and the triangular wave are used for evaluation. A noisy ECG signal, corrupted by motion artifacts, is simulated by the addition of two types of random noise to the original ECG signal. For comparison, three indices for the other methods are also computed: mean, median and hard thresholding. The performance of the WIF shows that RSE, SNR and SD are 392.7, 18.3dB and 2.6, respectively, in the case of a noisy signal with an SNR of 7.1 dB. This result is much better than those for the other methods.

QT dispersion does not represent electrocardiographic interlead heterogeneity of ventricular repolarization

INTRODUCTION

QT dispersion (QTd, range of QT intervals in 12 ECG leads) is thought to reflect spatial heterogeneity of ventricular refractoriness. However, QTd may be largely due to projections of the repolarization dipole rather than "nondipolar" signals.

METHODS AND RESULTS

Seventy-eight normal subjects (47+/-16 years, 23 women), 68 hypertrophic cardiomyopathy patients (HCM; 38+/-15 years, 21 women), 72 dilated cardiomyopathy patients (DCM; 48+/-15 years, 29 women), and 81 survivors of acute myocardial infarction (AMI; 63+/-12 years, 20 women) had digital 12-lead resting supine ECGs recorded (10 ECGs recorded in each subject and results averaged). In each ECG lead, QT interval was measured under operator review by QT Guard (GE Marquette) to obtain QTd. QTd was expressed as the range, standard deviation, and highest-to-lowest quartile difference of QT interval in all measurable leads. Singular value decomposition transferred ECGs into a minimum dimensional time orthogonal space. The first three components represented the ECG dipole; other components represented nondipolar signals. The power of the T wave nondipolar within the total components was computed to measure spatial repolarization heterogeneity (relative T wave residuum, TWR). QTd was 33.6+/-18.3, 47.0+/-19.3, 34.8+/-21.2, and 57.5+/-25.3 msec in normals, HCM, DCM, and AMI, respectively (normals vs DCM: NS, other P < 0.009). TWR was 0.029%+/-0.031%, 0.067%+/-0.067%, 0.112%+/-0.154%, and 0.186%+/-0.308% in normals, HCM, DCM, and AMI (HCM vs DCM: NS, other P < 0.006). The correlations between QTd and TWR were r = -0.0446, 0.2805, -0.1531, and 0.0771 (P = 0.03 for HCM, other NS) in normals, HCM, DCM, and AMI, respectively.

CONCLUSION

Spatial heterogeneity of ventricular repolarization exists and is measurable in 12-lead resting ECGs. It differs between different clinical groups, but the so-called QT dispersion is unrelated to it.