Independent Association of Sudden Cardiac Death and the Tpeak-Tend Interval on Vectorcardiogram

The causes of Sudden Cardiac Death (SCD) are still uncertain in the field of electro-cardiology. Cardiac repolarization may be the instance in which fatal arrhythmias lead to SCD development. Cardiac disease has not been well treated, as it is the leading cause of death in industrialized nations. Correlation of the T wave length to Sudden Cardiac Death (SCD) has been demonstrated in recent studies, most notably in a meta-analysis published in 2017, (Tse, Gong, Wong, Georgopoulos, Letsas, Vassiliou, … Liu, 2017). However, this project is attempting to show independent association of the T wave and SCD. Independent association demonstrates some mechanism in the heart which is elongating the T wave and also causing SCD. Use of the Vectorcardiogram (VCG) is novel because of its consistency and accuracy over an Electrocardiogram (ECG). The VCG offers three independent orthogonal views of the electrical activity of the heart, thus limiting subjectivity, overlapping information, and noise. Each of the three views offer an X, Y, and Z axis; when plotted, the electrical activity is represented as loops in three dimensional space. The Tpeak-Tend interval (Tp-Te) is measured on these VCG loops via algorithms developed by the Tereshchenko laboratory (Alday, Hamilton, Li-Pershing, Thomas, Gonzales, Li … Tereshchenko, 2018). The data being analyzed was gathered from two prospective cohort studies, known as the Arteriosclerosis Risk In Communities (ARIC) and Cardiovascular Health Study (CHS), (Waks, Sitlani, Soliman, Kabir, Ghafoori, Biggs, …, Tereshchenko, 2016). These cohorts provide digital ECGs, large study sample (\u3e102,000 ECG readings), and repeat visits. The ten second ECG readings are mathematically transformed with the Kors Transformation Matrix, in order to provide the VCG which is then analyzed. Independent association of the Tp-Te interval and SCD will provide better predictors of SCD and the possibility of risk score development

Non-linear analysis of electrocardiogram tracings in detection of occult coronary artery disease

The general problem of identifying significant characteristics of a system by analyzing the properties of a signal emitted by that system is common to many disciplines, biological as well as physical. In general, achievement of a satisfactory solution depends on the capability of assigning membership of candidate signals to one of a number of mutually exclusive categories: In this study, a new technique of processing the standard electrocardiograms from human subjects has been developed. This technique employs a set of non-linear transformations which enable the assignment of electrocardiograms into one of two Mutually exclusive categories. The first category is that of patients with occult coronary artery disease; the second category is that of subjects free from coronary artery disease. An introduction to the conventional means for assessing the standard electrocardiogram is presented, and the limitations noted. The new method is then presented which consists in large part of combining non-linear signal processing with a topological re-orientation of conventional cartesian coordinates to yield a multi-vector space which offers an optimum degree of visual perceptibility. Moreover, in this new domain, the transformed EKG tracings taken from subjects free from coronary artery disease inhabit a closed area, represented by the annular space bounded by two tangent circles. It is then shown that EKG tracings taken from subjects with occult coronary artery disease exhibit patterns which protrude beyond the circular boundaries. The mathematical transformations are shown to be non-linear and non-analytic in terms of satisfying the Cauchy-Riemann conditions. The assumptions and constraints of the transformations are explored and practical considerations are examined. Preliminary results obtained to date from over 100 medical cases are presented and analyzed. The tentative findings reveal a high degree of promise for the detection of asymptomatic coronary candidates well in advance of myocardial infarction. Finally, further applications to other medical areas are explored including a discussion of potential applicability to the fields of pharmacology and neurology

Nonlinear Stochastic Modeling and Analysis of Cardiovascular System Dynamics - Diagnostic and Prognostic Applications

The purpose of this investigation is to develop monitoring, diagnostic and prognostic schemes for cardiovascular diseases by studying the nonlinear stochastic dynamics underlying complex heart system. The employment of a nonlinear stochastic analysis combined with wavelet representations can extract effective cardiovascular features, which will be more sensitive to the pathological dynamics instead of the extraneous noises. While conventional statistical and linear systemic approaches have limitations for capturing signal variations resulting from changes in the cardiovascular system states. The research methodology includes signal representation using optimal wavelet function design, feature extraction using nonlinear recurrence analysis, and local recurrence modeling for state prediction.Industrial Engineering & Managemen

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 159

This bibliography lists 257 reports, articles, and other documents introduced into the NASA scientific and technical information system in September 1976

Non-invasive fetal electrocardiogram : analysis and interpretation

High-risk pregnancies are becoming more and more prevalent because of the progressively higher age at which women get pregnant. Nowadays about twenty percent of all pregnancies are complicated to some degree, for instance because of preterm delivery, fetal oxygen deficiency, fetal growth restriction, or hypertension. Early detection of these complications is critical to permit timely medical intervention, but is hampered by strong limitations of existing monitoring technology. This technology is either only applicable in hospital settings, is obtrusive, or is incapable of providing, in a robust way, reliable information for diagnosis of the well-being of the fetus. The most prominent method for monitoring of the fetal health condition is monitoring of heart rate variability in response to activity of the uterus (cardiotocography; CTG). Generally, in obstetrical practice, the heart rate is determined in either of two ways: unobtrusively with a (Doppler) ultrasound probe on the maternal abdomen, or obtrusively with an invasive electrode fixed onto the fetal scalp. The first method is relatively inaccurate but is non-invasive and applicable in all stages of pregnancy. The latter method is far more accurate but can only be applied following rupture of the membranes and sufficient dilatation, restricting its applicability to only the very last phase of pregnancy. Besides these accuracy and applicability issues, the use of CTG in obstetrical practice also has another limitation: despite its high sensitivity, the specificity of CTG is relatively low. This means that in most cases of fetal distress the CTG reveals specific patterns of heart rate variability, but that these specific patterns can also be encountered for healthy fetuses, complicating accurate diagnosis of the fetal condition. Hence, a prerequisite for preventing unnecessary interventions that are based on CTG alone, is the inclusion of additional information in diagnostics. Monitoring of the fetal electrocardiogram (ECG), as a supplement of CTG, has been demonstrated to have added value for monitoring of the fetal health condition. Unfortunately the application of the fetal ECG in obstetrical diagnostics is limited because at present the fetal ECG can only be measured reliably by means of an invasive scalp electrode. To overcome this limited applicability, many attempts have been made to record the fetal ECG non-invasively from the maternal abdomen, but these attempts have not yet led to approaches that permit widespread clinical application. One key difficulty is that the signal to noise ratio (SNR) of the transabdominal ECG recordings is relatively low. Perhaps even more importantly, the abdominal ECG recordings yield ECG signals for which the morphology depends strongly on the orientation of the fetus within the maternal uterus. Accordingly, for any fetal orientation, the ECG morphology is different. This renders correct clinical interpretation of the recorded ECG signals complicated, if not impossible. This thesis aims to address these difficulties and to provide new contributions on the clinical interpretation of the fetal ECG. At first the SNR of the recorded signals is enhanced through a series of signal processing steps that exploit specific and a priori known properties of the fetal ECG. More particularly, the dominant interference (i.e. the maternal ECG) is suppressed by exploiting the absence of temporal correlation between the maternal and fetal ECG. In this suppression, the maternal ECG complex is dynamically segmented into individual ECG waves and each of these waves is estimated through averaging corresponding waves from preceding ECG complexes. The maternal ECG template generated by combining the estimated waves is subsequently subtracted from the original signal to yield a non-invasive recording in which the maternal ECG has been suppressed. This suppression method is demonstrated to be more accurate than existing methods. Other interferences and noise are (partly) suppressed by exploiting the quasiperiodicity of the fetal ECG through averaging consecutive ECG complexes or by exploiting the spatial correlation of the ECG. The averaging of several consecutive ECG complexes, synchronized on their QRS complex, enhances the SNR of the ECG but also can suppress morphological variations in the ECG that are clinically relevant. The number of ECG complexes included in the average hence constitutes a trade-off between SNR enhancement on the one hand and loss of morphological variability on the other hand. To relax this trade-off, in this thesis a method is presented that can adaptively estimate the number of ECG complexes included in the average. In cases of morphological variations, this number is decreased ensuring that the variations are not suppressed. In cases of no morphological variability, this number is increased to ensure adequate SNR enhancement. The further suppression of noise by exploiting the spatial correlation of the ECG is based on the fact that all ECG signals recorded at several locations on the maternal abdomen originate from the same electrical source, namely the fetal heart. The electrical activity of the fetal heart at any point in time can be modeled as a single electrical field vector with stationary origin. This vector varies in both amplitude and orientation in three-dimensional space during the cardiac cycle and the time-path described by this vector is referred to as the fetal vectorcardiogram (VCG). In this model, the abdominal ECG constitutes the projection of the VCG onto the vector that describes the position of the abdominal electrode with respect to a reference electrode. This means that when the VCG is known, any desired ECG signal can be calculated. Equivalently, this also means that when enough ECG signals (i.e. at least three independent signals) are known, the VCG can be calculated. By using more than three ECG signals for the calculation of the VCG, redundancy in the ECG signals can be exploited for added noise suppression. Unfortunately, when calculating the fetal VCG from the ECG signals recorded from the maternal abdomen, the distance between the fetal heart and the electrodes is not the same for each electrode. Because the amplitude of the ECG signals decreases with propagation to the abdominal surface, these different distances yield a specific, unknown attenuation for each ECG signal. Existing methods for estimating the VCG operate with a fixed linear combination of the ECG signals and, hence, cannot account for variations in signal attenuation. To overcome this problem and be able to account for fetal movement, in this thesis a method is presented that estimates both the VCG and, to some extent, also the signal attenuation. This is done by determining for which VCG and signal attenuation the joint probability over both these variables is maximal given the observed ECG signals. The underlying joint probability distribution is determined by assuming the ECG signals to originate from scaled VCG projections and additive noise. With this method, a VCG, tailored to each specific patient, is determined. With respect to the fixed linear combinations, the presented method performs significantly better in the accurate estimation of the VCG. Besides describing the electrical activity of the fetal heart in three dimensions, the fetal VCG also provides a framework to account for the fetal orientation in the uterus. This framework enables the detection of the fetal orientation over time and allows for rotating the fetal VCG towards a prescribed orientation. From the normalized fetal VCG obtained in this manner, standardized ECG signals can be calculated, facilitating correct clinical interpretation of the non-invasive fetal ECG signals. The potential of the presented approach (i.e. the combination of all methods described above) is illustrated for three different clinical cases. In the first case, the fetal ECG is analyzed to demonstrate that the electrical behavior of the fetal heart differs significantly from the adult heart. In fact, this difference is so substantial that diagnostics based on the fetal ECG should be based on different guidelines than those for adult ECG diagnostics. In the second case, the fetal ECG is used to visualize the origin of fetal supraventricular extrasystoles and the results suggest that the fetal ECG might in future serve as diagnostic tool for relating fetal arrhythmia to congenital heart diseases. In the last case, the non-invasive fetal ECG is compared to the invasively recorded fetal ECG to gauge the SNR of the transabdominal recordings and to demonstrate the suitability of the non-invasive fetal ECG in clinical applications that, as yet, are only possible for the invasive fetal ECG

Derivation of respiration from electrocardiogram during heart rate variability studies

A method was developed to derive the respiration signal from the ECG signal based on the observation that the body-surface ECG is influenced by electrode motion relative to the heart and that fluctuations in the mean cardiac electrical axis accompany respiration. S-Plus programs were developed to calculate the changes in the value of the mean cardiac electrical axis during respiration from a two lead ECG signal and to generate a continuous ECG-derived respiratory signal from the angle information. Data were taken from 9 healthy subjects during rest, paced breathing and exercise. The respiration was derived from the recorded ECG signals. The ECG-derived respiration was compared with the original respiration recorded through an impedance pneumography device. The derived respiration shows an excellent correspondence with the original respiration. Statistical analysis indicates that the ECG-derived respiration has a high correlation with the original respiration in the frequency domain. Our study provides a method to obtain the respiration from the ECG signal when respiration information is not directly available. This can be done either directly or from a Holter recording. It is therefore possible to do spectral analysis of heart rate variability and determine the frequency of the spectral peak occurring at the respiration frequency

Alternative Lead Systems for Diagnostic Electrocardiography: Validation and Clinical Applicability

The standard 12-lead electrocardiogram (ECG) remains one of the most important and most frequently used tools for diagnosing cardiac diseases, although several different examination modalities in cardio¬logy have been developed over the years. The standard ECG uses 10 electrodes placed on well-defined positions on the body, 6 on the torso and 4 distally on the limbs. Both industry and academia have invested many years in development of the criteria used to interpret the “diagnostic” standard ECG, and the waveform patterns are taught in medical school. In several situations, however – such as during long-term ECG monitoring or stress testing – use of the electrode positions of the standard ECG is not optimal because of the abundance of noise. In these situations, the limb electrodes must be placed proximally, often even on the torso, and the Mason-Likar (M-L) positions are commonly used. Interference with other clinical procedures, such as echocardiography, can also constitute a problem. An ECG-recording system with fewer electrodes and without any electrodes on the limbs that provides a 12-lead ECG similar to the standard ECG would be valuable. The so-called EASI system uses only 4 recording electrodes in easily determined locations on the torso from which the full 12-lead ECG can be derived. The 12-lead ECG derived from the EASI system has been evaluated in adults in several clinical situations. Physicians who use ECGs in their day-to-day work are often not aware of the differences between 12-lead ECGs recorded from standard versus alternative electrode positions, and they might use criteria developed for the standard ECG when interpreting an ECG obtained from an alternative lead system. This can lead to misinterpretation with the risk of potentially serious consequences for the patient. Optimizing the proximal positions for better concordance with the standard ECG would be of great value for improved diagnostic performance. A version of the “Lund” (LU) lead system has been reported to agree better with the standard lead system than does the M-L lead system, with regard to both Q-wave width and QRS frontal plane axis. To develop a uniform convention for ECG recording, i.e. both for diagnostic ECG and for monitoring, a recording must produce waveforms that have morphologies approximating those obtained with standard ECG and that has noise immunity close to that of M-L. The overall objectives of this thesis were 1) to further validate the EASI system to gain more knowledge about the agreement between EASI-derived and standard 12-lead ECGs, and 2) to investigate the possibility of optimizing the positions of proximally placed limb electrodes. EASI studies In Study I, age-specific transformation coefficients were determined for use in deriving 12-lead ECGs from the EASI signals. The agreement of the waveforms between simultaneously recorded standard and EASI-derived 12-lead ECGs in children (healthy and with various cardiac diagnoses) was studied. For children, it was better to use age-specific transformation coefficients than adult coefficients. The agreement between standard and EASI-derived ECGs was mostly good. In Study II, the intrareader variation of interpretations of 2 standard 12-lead ECGs was compared with the variation of interpretations of standard versus EASI-derived 12-lead ECGs in children (Study I population). The variation of the interpretation of standard versus EASI-derived ECGs was only slightly larger than the intrareader variation of interpretations of standard ECGs. In Study III, the amplitudes of myoelectric noise and baseline wander were compared between simultaneously recorded EASI-derived and M-L 12-lead ECGs in healthy adults. Overall, the 2 lead systems had similar susceptibilities to baseline wander, but EASI was less susceptible than M-L to myoelectric noise. In Study IV, differences in the estimated size of myocardial infarction (MI), as assessed by Selvester scores, were compared between standard and EASI-derived 12-lead ECGs among patients who had had an episode of chest pain suggestive of an acute coronary syndrome. These scores were also compared with MI size measured by cardiac magnetic resonance imaging (MRI). Estimated MI size did not differ significantly between the 2 lead systems, but neither the correlation nor the agreement between MRI and either of the 2 lead systems was very strong. Study to optimize the proximal positions of the limb electrodes In Study V, waveforms from the LU and M-L systems were compared with those from standard ECGs with regard to the QRS axis in the frontal plane and QRS changes of inferior MI. The noise immunities of the standard, LU, and M-L systems were also compared. LU produced ECG waveforms that more closely resembled those obtained with standard ECG than did M-L. The LU system was more noise-immune than was the standard system, and the noise immunities of the LU and the M-L systems were comparable

Reconstructing Electrocardiogram Leads From a Reduced Lead Set Through the Use of Patient-Specific Transforms and Independent Component Analysis

In this exploration into electrocardiogram (ECG) lead reconstruction, two algorithms were developed and tested on a public database and in real-time on patients. These algorithms were based on independent component analysis (ICA). ICA was a promising method due to its implications for spatial independence of lead placement and its adaptive nature to changing orientation of the heart in relation to the electrodes. The first algorithm was used to reconstruct missing precordial leads, which has two key applications. The first is correcting precordial lead measurements in a standard 12-lead configuration. If an irregular signal or high level of noise is detected on a precordial lead, the obfuscated signal can be calculated from other nearby leads. The second is the reduction in the number of precordial leads required for accurate measurement, which opens up the surface of the chest above the heart for diagnostic procedures. Using only two precordial leads, the other four were reconstructed with a high degree of accuracy. This research was presented at the 33rd International Conference of the IEEE Engineering in Medicine and Biology Society in 2011.1 The second algorithm was developed to construct a full 12-lead clinical ECG from either three differential measurements or three standard leads. By utilizing differential measurements, the ECG could be reconstructed using wireless systems, which lack the common ground necessary for the standard measurement method. Using three leads distributed across the expanse of the space of the heart, all twelve leads were successfully reconstructed and compared against state of the art algorithms. This work has been accepted for publication in the IEEE Journal of Biomedical and Health Informatics.2 These algorithms show a proof of concept, one which can be further honed to deal with the issues of sorting independent components and improving the training sequences. This research also revealed the possibility of extracting and monitoring additional physiological information, such as a patient\u27s breathing rate from currently utilized ECG systems

Analysis of Ventricular Depolarisation and Repolarisation Using Registration and Machine Learning

Our understanding of cardiac diseases has greatly advanced since the advent of electrocardiography (ECG). With the increasing influx of available data in recent times, significant research efforts have been put forth to automate the study and detection of cardiac conditions. Naturally, the focus has progressed toward studying dynamic changes in ventricular depolarisation and repolarisation across serial recordings - as complex beat-to-beat changes in morphology manifest over time. Manual extraction of diagnostic and prognostic markers is a laborious task. Hence, automated and accurate methods are required to extract markers for the study of ventricular lability and detection of common diseases, such as myocardial ischemia and myocardial infarction. The aim of this thesis is to improve automated marker extraction and detection of diseases for the study of ventricular depolarisation and repolarisation lability in ECG. As such, two novel template adaptation methods capable of capturing complex beat-to-beat morphological changes are proposed for three-dimensional and two-dimensional data, respectively. The proposed three-dimensional template adaptation method provides an inhomogeneous method for transforming template vectorcardiogram (VCG) by exploiting registrationinspired parametrisation and an efficient kernel ridge regression formulation. Analysis across simulated data and clinical myocardial infarction data demonstrates state-of-the-art results. The two-dimensional template adaptation method draws from traditional registrationbased techniques and treats the ECG as a two-dimensional point set problem. Validation against previously employed simulated data and a gold-standard annotated clinical database demonstrate the highest level of performance. Subsequently, frameworks employing the proposed template adaptation techniques are developed for the automated detection of ischemic beats and myocardial infarction. Furthermore, a small study analysing ventricular repolarisation variability (VRV) in non-ischemic cardiomyopathy (CM) is considered, utilising markers of cardiac lability proposed in the development of the three-dimensional template adaptation system. In summary, this thesis highlights the necessity for custom template adaptation methods for the accurate measurement of beat-to-beat variability in cardiac data. Two novel stateof- the-art methods are proposed and extended to study myocardial ischemia, myocardial infarction and non-ischemic CM.Thesis (Ph.D.) -- University of Adelaide, School of Electrical and Electronic Engineering, 202