Search

In this paper, an attempt is made to simulate and compare spatio-temporal VCG and VMCG derived from epicardial potentials. Electric (EHV) and Magnetic heart vectors (MHV) are computed from the ECG and MCG at various time instants and their orientations with respect to time are found to show a reasonable tilt of 90 to 100 degrees. The complimentary information with reference to the orientation of cardiac vector offered by MHV could be attributed to its sensitivity to intracellular myocardial currents, while EHV exhibits the orientation associated with only the extracellular currents owing to volume conduction. By comparing the orientations of EHV and MHV generated from a simulated equivalent current dipole model, the present work demonstrates the usefulness of these spatiotemporal vectors in tracing the cardiac current flow inside the thorax for a healthy heart. It could be thus expected that clinically relevant information could be obtained if the present analysis is extended to highly complex and irregular cardiac activation sequences that could be seen in arrhythmia and myocardial infarction. The main contribution of this paper is to mathematically model and derive the magnetic heart vectors from the MCG system extracted from IGCAR lab and verify it with the conventional VCG extraction.. [ABSTRACT FROM AUTHOR]

In this paper, the inverse problems of cardiac sources using analytical and probabilistic methods are solved and discussed. The standard Tikhonov regularization technique is solved initially to estimate the under-determined heart surface potentials from Magnetocardiographic (MCG) signals. The results of the deterministic method subjected to noise in the measurements are discussed and compared with the probabilistic models. Hierarchical Bayesian modeling with fixed Gaussian prior is employed to quantify the uncertainties in source reconstructions. A novel application of Variational Bayesian inference approach has been presented to estimate the heart sources. The reconstruction results of Variational Bayesian model with non-stationary priors are compared with solutions of simplistic Bayesian approach; and the performances are evaluated using Root Mean Square Error (RMSE) and correlation co-efficient metrics. The Bayesian solutions in the study are also extended to localize the MCG sources for two types of Myocardial infarction cases. [ABSTRACT FROM AUTHOR]

The electrical impulses of the heart will generate a tiny magnetic field outside the thorax that is measured as Magnetocardiographic signals. The challenging study is to estimate the cardiac activities in terms of depolarisation and repolarization maps from the measured signals called as inverse problem. This is computed only if one has solved generic or subject- specific prior models using the anatomical structures of the myocardium, the torso and the detectors called as forward problem. In this study, the Discretised heart is priorily assumed as the dipolar sources forming a double layer. The thorax structure modelled with finite element meshes is considered in the forward study. The magnetocardiographic data are simulated using uniform double layer model representing transmembrane distribution on the epicardium and endocardium. Using this data, the activation maps are non-invasively imaged on the heart surface using Tikhonov's regularisation technique. The inverse study is extended to reconstruct the depolarisation sequences of the abnormal cases. [ABSTRACT FROM AUTHOR]