Beat-to-beat measurement and analysis of the R-T interval in 24 h ECG Holter recordings

Multivariate Correlation Measures Reveal Structure and Strength of Brain-Body Physiological Networks at Rest and During Mental Stress

In this work, we extend to the multivariate case the classical correlation analysis used in the field of network physiology to probe dynamic interactions between organ systems in the human body. To this end, we define different correlation-based measures of the multivariate interaction (MI) within and between the brain and body subnetworks of the human physiological network, represented, respectively, by the time series of δ, θ, α, and β electroencephalographic (EEG) wave amplitudes, and of heart rate, respiration amplitude, and pulse arrival time (PAT) variability (η, ρ, π). MI is computed: (i) considering all variables in the two subnetworks to evaluate overall brain-body interactions; (ii) focusing on a single target variable and dissecting its global interaction with all other variables into contributions arising from the same subnetwork and from the other subnetwork; and (iii) considering two variables conditioned to all the others to infer the network topology. The framework is applied to the time series measured from the EEG, electrocardiographic (ECG), respiration, and blood volume pulse (BVP) signals recorded synchronously via wearable sensors in a group of healthy subjects monitored at rest and during mental arithmetic and sustained attention tasks. We find that the human physiological network is highly connected, with predominance of the links internal of each subnetwork (mainly η-ρ and δ-θ, θ-α, α-β), but also statistically significant interactions between the two subnetworks (mainly η-β and η-δ). MI values are often spatially heterogeneous across the scalp and are modulated by the physiological state, as indicated by the decrease of cardiorespiratory interactions during sustained attention and by the increase of brain-heart interactions and of brain-brain interactions at the frontal scalp regions during mental arithmetic. These findings illustrate the complex and multi-faceted structure of interactions manifested within and between different physiological systems and subsystems across different levels of mental stress.

Transformable Electrocardiograph Using Robust Liquid-Solid Heteroconnector

In this study, a highly transformable electrocardiograph that can considerably deform the position of stretchable electrodes based on the lead method for diagnosing heart disease was developed; these electrodes exhibited high resistance stability against considerable stretching and multiple stretching. To realize the large deformable functionality of the electrodes of a system, liquid metal electrodes and a heteroconnector composed of a liquid metal paste and carbon-based conductive rubber were employed. The developed device can achieve a 200% strain with only 6% resistance change and a high stability of resistances after the 100-time stretching test. In addition, the study demonstrated electrocardiograms in different lead methods of adult and child using the same device. The proposed combination of large deformable electrodes with high electric stability and a robust heteroconnector is an important technology, and it presents a considerable advancement in the application of stretchable electronic systems.

Concomitant Evaluation of Heart Period and QT Interval Variability Spectral Markers to Typify Cardiac Control in Humans and Rats

The variability of heart period, measured as the time distance between two consecutive QRS complexes from the electrocardiogram (RR), was exploited to infer cardiac vagal control, while the variability of the duration of the electrical activity of the heart, measured as the time interval from Q-wave onset to T-wave end (QT), was proposed as an indirect index of cardiac sympathetic modulation. This study tests the utility of the concomitant evaluation of RR variability (RRV) and QT variability (QTV) markers in typifying cardiac autonomic control of humans under different experimental conditions and of rat groups featuring documented differences in resting sympatho-vagal balance. We considered: (i) 23 healthy young subjects in resting supine position (REST) undergoing head-up tilt at 45° (T45) and 90° (T90) followed by recovery to the supine position; (ii) 9 Wistar (WI) and 14 wild-type Groningen (WT) rats in unstressed conditions, where the WT animals were classified as non-aggressive (non-AGG, n = 9) and aggressive (AGG, n = 5) according to the resident intruder test. In humans, spectral analysis of RRV and QTV was performed over a single stationary sequence of 250 consecutive values. In rats, spectral analysis was iterated over 10-min recordings with a frame length of 250 beats with 80% overlap and the median of the distribution of the spectral markers was extracted. Over RRV and QTV we computed the power in the low frequency (LF, from 0.04 to 0.15 Hz in humans and from 0.2 to 0.75 Hz in rats) band (LF_RR and LF_QT) and the power in the high frequency (HF, from 0.15 to 0.5 Hz in humans and from 0.75 to 2.5 Hz in rats) band (HF_RR and HF_QT). In humans the HF_RR power was lower during T90 and higher during recovery compared to REST, while the LF_QT power was higher during T90. In rats the HF_RR power was lower in WT rats compared to WI rats and the LF_QT power was higher in AGG than in non-AGG animals. We concluded that RRV and QTV provide complementary information in describing the functioning of vagal and sympathetic limbs of the autonomic nervous system in humans and rats.

Information Dynamics of the Brain, Cardiovascular and Respiratory Network during Different Levels of Mental Stress

In this study, an analysis of brain, cardiovascular and respiratory dynamics was conducted combining information-theoretic measures with the Network Physiology paradigm during different levels of mental stress. Starting from low invasive recordings of electroencephalographic, electrocardiographic, respiratory, and blood volume pulse signals, the dynamical activity of seven physiological systems was probed with one-second time resolution measuring the time series of the δ, θ, α and β brain wave amplitudes, the cardiac period (RR interval), the respiratory amplitude, and the duration of blood pressure wave propagation (pulse arrival time, PAT). Synchronous 5-min windows of these time series, obtained from 18 subjects during resting wakefulness (REST), mental stress induced by mental arithmetic (MA) and sustained attention induced by serious game (SG), were taken to describe the dynamics of the nodes composing the observed physiological network. Network activity and connectivity were then assessed in the framework of information dynamics computing the new information generated by each node, the information dynamically stored in it, and the information transferred to it from the other network nodes. Moreover, the network topology was investigated using directed measures of conditional information transfer and assessing their statistical significance. We found that all network nodes dynamically produce and store significant amounts of information, with the new information being prevalent in the brain systems and the information storage being prevalent in the peripheral systems. The transition from REST to MA was associated with an increase of the new information produced by the respiratory signal time series (RESP), and that from MA to SG with a decrease of the new information produced by PAT. Each network node received a significant amount of information from the other nodes, with the highest amount transferred to RR and the lowest transferred to δ, θ, α and β. The topology of the physiological network underlying such information transfer was node- and state-dependent, with the peripheral subnetwork showing interactions from RR to PAT and between RESP and RR, PAT consistently across states, the brain subnetwork resulting more connected during MA, and the subnetwork of brain–peripheral interactions involving different brain rhythms in the three states and resulting primarily activated during MA. These results have both physiological relevance as regards the interpretation of central and autonomic effects on cardiovascular and respiratory variability, and practical relevance as regards the identification of features useful for the automatic distinction of different mental states.

A Real-Time QRS Detection System With PR/RT Interval and ST Segment Measurements for Wearable ECG Sensors Using Parallel Delta Modulators

This paper presents a real-time electrocardiogram (ECG) monitoring system for wearable devices. The system is based on the proposed parallel delta modulator architecture with local maximum point and local minimum point algorithms to detect QRS and PT waves. Therefore, using the proposed system and algorithm, real-time PR and RT intervals, and ST segment measurements can be achieved in long-term wearable ECG recording. The algorithm is tested with the MIT-BIH Arrhythmia Database for QRS complex detection and with the QT Database for the P and T wave detections. The simulation result shows that the algorithm achieves above 99%, 91%, and 98% accuracy in the QRS complex, P wave, and T wave detections, respectively. Experimental results are presented from the system prototype, in which the parallel delta modulator circuits are fabricated in IBM 0.13 $\mu \text{m}$ standard CMOS technology and the algorithms are implemented in a Xilinx Spartan-6 field programmable gate array (FPGA). The parallel delta modulators consume 720 nW at 1 kHz sampling rate with $\pm$0.6 V power supply. The proposed system has the potential to be applied in future long-term wearable ECG recording devices.

A network physiology approach to the assessment of the link between sinoatrial and ventricular cardiac controls

OBJECTIVE

A network physiology approach to evaluate the strength of the directed interactions among cardiac controls at sinoatrial and ventricular levels and respiration (R) is proposed.

APPROACH

The network is composed of three nodes (i.e. sinoatrial and ventricular cardiac controls and R) and their activity is exemplified by the variability of heart period (HP), the variability of the duration of the electrical activity of the heart approximated as the temporal distance between Q-wave onset and T-wave end or apex (i.e. QTe or QTa) and thoracic movements respectively. Model-based transfer entropy provided the estimate of the strength of the causal link from the source to the destination conditioned on the remaining node activity. The interactions were monitored in 15 healthy subjects aged from 24 to 54 years (9 males). Increasing levels of sympathetic activity were induced by graded head-up tilt with table inclination of 0, 15, 30, 45, 60, 75°.

MAIN RESULTS

We found that: (i) the strength of the causal link from HP to QTe gradually decreases with tilt table angle, while that in the reverse direction is weak, even though significant, and constant; (ii) the action of R on HP is stronger than that from R to QTe; (iii) the strength of the relation from R to HP is weakly related to tilt table inclination, while that from R to QTe does not depend on it; (iv) while QTe cannot affect R, a weak causal dependence of R on HP is detected; (v) the network computed over QTa is qualitatively similar to that over QTe, even though the strength of the causal relations might be different.

SIGNIFICANCE

The proposed network physiology approach provides a comprehensive picture of the directed links among relevant cardiac regulatory mechanisms and their evolution with sympathetic tone usable to identify pathological conditions.

Reliability of Lagged Poincaré Plot Parameters in Ultrashort Heart Rate Variability Series: Application on Affective Sounds

The number of studies about ultrashort cardiovascular time series is increasing because of the demand for mobile applications in telemedicine and e-health monitoring. However, the current literature still needs a proper validation of heartbeat nonlinear dynamics assessment from ultrashort time series. This paper reports on the reliability of the Lagged Poincaré Plot (LPP) parameters-calculated from ultrashort cardiovascular time series. Reliability is studied on simulated as well as on real RR series. Simulated RR series are generated and LPP parameters estimated for ultrashort time series (from 15 to 60 s) are compared to those estimated from 1 h. All LPP parameters estimated from time series longer than 35 s presented a Spearman's correlation coefficient higher than 0.99. RR series acquired from 32 healthy subjects during 5-min resting state sessions are used to test the LPP approach in experimental data. The usefulness of ultrashort term parameters in real data is accomplished also studying their ability to discriminate positive and negative valence of auditory stimuli taken from the International Affective Digitized Sound System (IADS) dataset. The achieved accuracies in the recognition of elicitation along the valence dimension, using only the LPP parameters, were of 77.78% for 1 min 28 s series, and of 79.17% for 35 s series.

QT interval variability in body surface ECG: measurement, physiological basis, and clinical value: position statement and consensus guidance endorsed by the European Heart Rhythm Association jointly with the ESC Working Group on Cardiac Cellular Electrophysiology

This consensus guideline discusses the electrocardiographic phenomenon of beat-to-beat QT interval variability (QTV) on surface electrocardiograms. The text covers measurement principles, physiological basis, and clinical value of QTV. Technical considerations include QT interval measurement and the relation between QTV and heart rate variability. Research frontiers of QTV include understanding of QTV physiology, systematic evaluation of the link between QTV and direct measures of neural activity, modelling of the QTV dependence on the variability of other physiological variables, distinction between QTV and general T wave shape variability, and assessing of the QTV utility for guiding therapy. Increased QTV appears to be a risk marker of arrhythmic and cardiovascular death. It remains to be established whether it can guide therapy alone or in combination with other risk factors. QT interval variability has a possible role in non-invasive assessment of tonic sympathetic activity.

Towards a better understanding of QT interval variability

The International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) Guideline E14 recommends 'Thorough QT Study' as a standard assessment of drug-induced QT interval prolongation. At the same time, the value of drug-induced QTc prolongation as a surrogate marker for risk of life-threatening polymorphic ventricular tachycardia known as torsades des pointes remains controversial. Beat-to-beat variability of QT interval was recently proposed as an alternative metric. The following review addresses mechanisms of beat-to-beat QT variability, methods of QT interval variability measurements, and its prognostic value in clinical studies.

Development of a feedback stimulation for drowsy driver using heartbeat rhythms

We investigated the physiological response of a vibratory stimulation, which has the rhythm of heartbeats, and examined whether it is useful for the feedback stimulation for drowsy driving. We evaluated the efficiency of 4 types of vibratory rhythms for stimulation by using the sleepiness level estimated by the multiple linear regression model made from the indices of ECG and respiration. As the result, the vibratory rhythm, which has the real time heartbeats of subjects themselves, had an effect of inducing their physiological condition closer to the condition when they were struggling against the drowsiness. We concluded that the stimulation might be useful to prevent a drowsy driving if we could give it to the driver before he or she gets the severe drowsiness.

Cardiac regulation and electrocardiographic factors contributing to the measurement of repolarization variability

Cellular and macroelectrical instability within the heart ventricles during repolarization is described as a potential triggering mechanism of life-threatening arrhythmias. Although this phenomenon was observed in animal and in vitro studies, significant efforts have been put into the design of computerized technologies to quantify very subtle variations of the repolarization signal from the surface electrocardiograms. These technologies aim at capturing repolarization instability of ventricular repolarization while controlling for the normal variability. Currently, the methods have focused on the autonomic regulation of the heart rate as a primary confounding factor (such as in the QT variability index). However, there are other factors that can influence the measurements of beat-to beat variability of the repolarization segment. Among them, the amplitude of the repolarization signal, the selected lead, and the heart vector orientation are very important and too often neglected in clinical investigations. We will discuss these factors and provocatively describe why they should be cautiously considered to avoid erroneous measurements of repolarization instability.

Measurement and regulation of cardiac ventricular repolarization: from the QT interval to repolarization morphology

Ventricular repolarization (VR) is a crucial step in cardiac electrical activity because it corresponds to a recovery period setting the stage for the next heart contraction. Small perturbations of the VR process can predispose an individual to lethal arrhythmias. In this review, I aim to provide an overview of the methods developed to analyse static and dynamic aspects of the VR process when recorded from a surface electrocardiogram (ECG). The first section describes the list of physiological and clinical factors that can affect the VR. Technical aspects important to consider when digitally processing ECGs are provided as well. Special attention is given to the analysis of the effect of heart rate on the VR and its regulation by the autonomic nervous system. The final section provides the rationale for extending the analysis of the VR from its duration to its morphology. Several modelling techniques and measurement methods will be presented and their role within the arena of cardiac safety will be discussed.

Effects of RR segment duration on HRV spectrum estimation

Although patterns of heart rate variability (HRV) hold considerable promise for clarifying issues in clinical applications, the inappropriate quantification and interpretation of these patterns may obscure critical issues or relationships and may impede rather than foster the development of clinical applications. The duration of the RR interval series is not a matter of convenience but a fine balance between two important issues: acceptable variance and stationarity of the time series on one hand, and acceptable resolution of the spectral estimate and reduced spectral leakage on the other. Further, in the standard short-term HRV analysis, it has been observed that the previous studies in HRV spectral analysis use a wide range of RR interval segment duration for spectral estimation by Welch's algorithm. The standardization of RR interval segment duration is also important for comparisons among studies and is essential for within-study experimental contrasts. In the present study, a comparative analysis for RR interval segment durations has been made to propose an optimal RR interval segment duration. Firstly a simulated signal was analyzed with Hann window and zero padding for the segment lengths of 1024, 512, 256 and 128 samples resampled at 4 Hz with 50% overlapping. Again, the above procedure was applied to RR interval series and it was concluded that segment length of 256 samples with 50% overlapping provides a smoothed spectral estimate with clearly outlined peaks in low- and high-frequency bands. This easily understandable and interpretable spectral estimate leads to a better visual and automated analysis, which is not only desirable in basic physiology studies, but also a prerequisite for a widespread utilization of frequency domain techniques in clinical studies, where simplicity and effectiveness of information are of primary importance.

A wavelet-based ECG delineator: evaluation on standard databases

In this paper, we developed and evaluated a robust single-lead electrocardiogram (ECG) delineation system based on the wavelet transform (WT). In a first step, QRS complexes are detected. Then, each QRS is delineated by detecting and identifying the peaks of the individual waves, as well as the complex onset and end. Finally, the determination of P and T wave peaks, onsets and ends is performed. We evaluated the algorithm on several manually annotated databases, such as MIT-BIH Arrhythmia, QT, European ST-T and CSE databases, developed for validation purposes. The QRS detector obtained a sensitivity of Se = 99.66% and a positive predictivity of P+ = 99.56% over the first lead of the validation databases (more than 980,000 beats), while for the well-known MIT-BIH Arrhythmia Database, Se and P+ over 99.8% were attained. As for the delineation of the ECG waves, the mean and standard deviation of the differences between the automatic and manual annotations were computed. The mean error obtained with the WT approach was found not to exceed one sampling interval, while the standard deviations were around the accepted tolerances between expert physicians, outperforming the results of other well known algorithms, especially in determining the end of T wave.

T wave spectral variance for noninvasive identification of patients with idiopathic dilated cardiomyopathy prone to ventricular fibrillation even in the presence of bundle branch block or atrial fibrillation

Conventional methods using Holter ECG recordings for noninvasive risk stratification are limited in patients with idiopathic dilated cardiomyopathy (IDC) prone to ventricular fibrillation (VF) having atrial fibrillation (AF) or bundle branch block (BBB). We therefore investigated, whether spectral assessment of beat-to-beat alternations of repolarization is associated with VF in these patients. Twenty-four-hour Holter ECG recordings in 462 patients with IDC were used. The VF group comprised of 64 consecutive patients who survived cardiac arrest, the no VF group consisted of 398 consecutive patients without a history of malignant ventricular arrhythmia. One hundred patients with ischemic cardiomyopathy (ICM) served as a control group. In each patient, 1,024 consecutive T waves were aligned using cross correlation methods. Two-dimensional Fourier transform (2D FFT) used the data matrix of 1,024 consecutive 200-ms segments centered to the T wave peak. Power spectra of the 2D FFT revealed the frequency content of the T wave in the first dimension and the periodicity of this frequency content in the second dimension. The ratio between periodic frequency contents and the sum of nonperiodic and periodic frequency contents between 0.5 and 50 Hz is equal to the T wave spectral variance (TWSV) index. Thus, TWSV index = 0 would mean that all 1,024 T waves are identical and TWSV index = 1 would mean that the 1,024 T waves are totally variable. The TWSV index was significantly higher in the VF group (0.93 +/- 0.14) than in the no VF group (0.53 +/- 0.13, P < 0.01). The best cutoff between the VF and the no VF group was achieved by using a TWSV index of 0.75 (sensitivity = 89%, specificity = 78%). No significant differences were observed between patients with and without AF or with and without BBB, and between patients with IDC and ICM. Even in the presence of BBB or AF spectral assessment of T wave alternations by TWSV index using 2D FFT in Holter ECG recordings, allows the identification of patients with IDC at risk for VF.

Independent autonomic modulation of sinus node and ventricular myocardium in healthy young men during sleep

INTRODUCTION

The aim of this study was to investigate whether autonomic modulation of ventricular repolarization may spontaneously differ from that of the sinoatrial node.

METHODS AND RESULTS

Onset of P waves, QRS complexes, and the apex and end of T waves were detected beat to beat in high-resolution ECGs from nine healthy young men during the night. There were time-dependent fluctuations in the QT/RR slopes of consecutive 5-minute segments that could not be explained by the mean RR cycle length of the respective segment. Because the variability found in QT intervals could not be explained by either possible effects of rate dependence or hysteresis, autonomic effects were obvious. Power spectral analysis was performed for consecutive 5-minute segments of PP and QT tachograms. In a given subject, trends in the time course of low-frequency (LF) and high-frequency (HF) power in PP and QT often were similar, but they were quite different at other times. The mean LF/HF ratio for QTend (0.75 +/- 0.1) was different from that of PP (1.8 +/- 0.2; P = 0.002), indicating differences in sympathovagal balance at the different anatomic sites. Furthermore, at a given mean heart rate, averaged QT intervals were different on a time scale of several minutes to hours. The QT/RR slope of 5-minute segments correlated significantly with the HF power of QT variability but not with that of PP variability, indicating effects of the autonomic nervous system on ventricular action potential restitution.

CONCLUSION

These differences demonstrate that changes in sinus node automaticity are not necessarily indicative of the autonomic control of ventricular myocardium.

Analysis of the ST-T complex of the electrocardiogram using the Karhunen--Loève transform: adaptive monitoring and alternans detection

The Karhunen-Loève transform (KLT) is applied to study the ventricular repolarisation period as reflected in the ST-T complex of the surface ECG. The KLT coefficients provide a sensitive means of quantitating ST-T shapes. A training set of ST-T complexes is used to derive a set of KLT basis vectors that permits representation of 90% of the signal energy using four KLT coefficients. As a truncated KLT expansion tends to favor representation of the signal over any additive noise, a time series of KLT coefficients obtained from successive ST-T complexes is better suited for representation of both medium-term variations (such as ischemic changes) and short-term variations (such as ST-T alternans) than discrete parameters such as the ST level or other local indices. For analysis of ischemic changes, an adaptive filter is described that can be used to estimate the KLT coefficient, yielding an increase in the signal-to-noise ratio of 10 dB (u = 0.1), with a convergence time of about three beats. A beat spectrum of the unfiltered KLT coefficient series is used for detection of ST-T alterans. These methods are illustrated with examples from the European ST-T Database. About 20% of records revealed quasi-periodic salvos of ischemic ST-T change episodes and another 20% exhibit repetitive, but not clearly periodic patterns of ST-T change episodes. About 5% of ischemic episodes were associated with ST-T alterans.

Using simulated noise to define optimal QT intervals for computer analysis of ambulatory ECG

The ambulatory electrocardiogram (ECG) is an important medical tool, not only for diagnosis of adverse cardiac events, but also to predict the risk of such events occurring. The 24-hour ambulatory ECG has certain problems and drawbacks because the signal is corrupted by noise from various sources and also several other conditions which may alter the ECG morphology. We have developed a Windows based program for the computer analysis of ambulatory ECG which attempts to address these problems. The software includes options for importing ECG data, different methods of waveform analysis, data-viewing, and exporting the extracted time series. In addition, the modular structure allows for flexible maintenance and expansion of the software. The ECG was recorded using a Holter device and oversampled to enhance the fidelity of the low sampling rate of the ambulatory ECG. The influence of different sampling rates on the interval variability were studied. The noise sensitivity of the implemented algorithm was tested with several types of simulated noise and the precision of the interval measurement was reported with SD values. Our simulations showed that, in most of the cases, defining the end of QT interval at the maximum of the T wave gave the most precise measurement. The definition of the onset of the ventricular repolarization duration is most precisely made on the maximum or descending maximal slope of the R wave. We also analyzed some examples of time series from patients using power spectrum estimates in order to validate the low level QT interval variability.

T wave spectral variance: A new method to determine inhomogeneous repolarization by T wave beat-to-beat variability in patients prone to ventricular arrhythmias

Inhomogeneous repolarization is considered to be associated with increased risk of ventricular arrhythmias, but exact determination of the end of the T wave is difficult, and a single measurement of the QTc interval may be insufficient for risk stratification. A new algorithm was therefore developed to determine the beat-to-beat variability of the T wave in Holter electrocardiographic recordings. This algorithm, termed T Wave Spectral Variance (TWSV) uses the two-dimensional fast Fourier transform to determine the beat-to-beat variability of the T wave in Hotter ECG recordings. The two-dimensional fast Fourier transform was calculated by use of a data matrix with 1,024 consecutive single beats (first dimension) and a 200-ms segment centered on the T wave (second dimension). The power spectra of the 2D-FFT revealed the frequency content of the T wave in the first dimension and the periodicity of these frequencies in cycles per beat in the second dimension. A TWSV index of periodicity was calculated by dividing total spectral energy by spectral energy at 0 cycles per beat. A TWSV index of 0 means a constant T wave from beat to beat; a TWSV index of 1 means a completely irregular T wave. Of the 200 patients investigated, all of whom had had myocardial infarctions, 50 had documented sustained ventricular tachycardia (VT) (<230 beats/min) (group 1), 50 had ventricular fibrillation (VF) (group 2), and 100 were without VT or VF (group 3); 10 normal subjects were also investigated. The visually determined QTc was 442 +/- 62 ms in group 1, 402 +/- 13 ms in group 2, 411 +/- 26 ms in group 3, and 398 +/- 43 ms in normal subjects (differences not significant). The TWSV index was 0.95 +/- 0.14 in group 1, 0.90 +/- 0.16 in group 2, and 0.64 +/- 0.24 in group 3; it showed a highly constant T wave in normal subjects (0.52 +/- 0.23). Differences between patients with VT and VF as against patients without VT or VF were significant (P < .05), whereas no statistical differences between patients with VT and VF could be found. Thus, TWSV, a new method to assess beat-to-beat variability of the T wave, revealed increased heterogeneity of repolarization in patients prone to both VT and VF after myocardial infarction, whereas a single QTc interval measurement showed no significant differences.

Performance assessment of standard algorithms for dynamic R-T interval measurement: comparison between R-Tapex and R-T(end) approach

Three automatic approaches to ventricular repolarisation duration measurement (R-Tapex, R-T(end threshold) and R-T(end fitting) methods) are compared on computer-generated and real ECG signals, in relation to their reliability in the presence of the most common electrocardiographic artefacts (i.e. additive broadband noise and additive and multiplicative periodical disturbances). Simulations permit the evaluation of the amount of R-T beat-to-beat variability induced by the artefacts. The R-T(end threshold) method performs better than the R-T(end fitting) one, and, hence, the latter should be used with caution when R-T(end) variability is addressed. Whereas the R-Tapex method is more robust with regard to broadband noise than the R-T(end threshold) one, the reverse situation is observed in the presence of periodical amplitude modulations. A high level of broadband noise dose not prevent the detection of the central frequency of underlying R-T periodical changes. Comparison between the power spectra of the beat-to-beat R-T variability series obtained from three orthogonal ECG leads (X,Y,Z) is used to assess the amount of real and artefactual variability in 13 normal subjects at rest. The R-Tapex series displays rhythms at high frequency (HF) with a percentage power on the Z lead (57.1 +/- 4.9) greater than that on the X and Y leads (41.9 +/- 4.6 and 46.1 +/- 4.9, respectively), probably because of respiratory-related artefacts affecting the Z lead more remarkably. More uniform HF power distributions over X,Y,Z leads are observed in the R-T(end threshold) series (31.8 +/- 3.8, 39.2 +/- 4.1 and 35.1 +/- 4.2, respectively), thus suggesting minor sensitivity of the R-T(end threshold) measure to respiratory-related artefacts.

Autonomic nervous system and sudden cardiac death

In the United States, sudden cardiac death is a major public health problem, accounting for approximately 300,000 deaths annually. Accurate identification of those patients at highest risk for this event has been problematic. The use of signal-averaged electrocardiography, Holter monitoring and assessment of left ventricular function have been shown to be predictive of future arrhythmic events in patients after a myocardial infarction. However, the clinical utility of these tests has been limited by their low sensitivity and positive predictive value. It has become increasingly clear that the autonomic nervous system is extremely important in the pathogenesis of ventricular arrhythmias and sudden cardiac death. The two most important techniques used to study the autonomic nervous system--heart rate variability and baroreflex sensitivity--are reviewed, and the clinical and experimental data suggesting that these techniques are powerful predictors of future arrhythmic events are discussed in depth.

Karhunen-Loève transform as a tool to analyze the ST-segment. Comparison with QT interval

The spatial and temporal courses of ventricular repolarization are quite sensitive to the biochemical and biophysiologic environment of the myocardial cells, and are therefore often an early marker of heart disease, particularly of ischemia. The detailed morphology of the surface electrocardiogram contains considerable information about the repolarization process. The ST-segment changes with ischemia, injury, and drugs. The QT interval is affected by drugs, heart rate, and autonomic tone, and in some situations may identify individuals at high risk for arrhythmias and sudden death. Variability in the shape, including duration, of the ST-T waves reflects autonomic nervous system activity and may identify high-risk patients. Automated methods for quantitatively characterizing ST-T complexes are important in studying long-term electrocardiographic records. Two computer-based measurement procedures for characterizing the repolarization period were comparatively analyzed: Karhunen-Loève (KL) transform representation of the ST-T shape and measurement of beat-to beat durations of repolarization (QT intervals). The results of KL transform representation and time-domain QT measurement algorithms for studying the repolarization period of the electrocardiogram on the European ST-T database are presented. It was found that about 20% of the records present a quasiperiodic KL pattern of ischemic ST-T activity and another 20% exhibit repetitive but not clearly periodic patterns of ischemic ST-T changes. From these ischemic records, 50% showed QT variations in at least one lead associated with the ischemic episodes.