Estimating electromechanical properties of the heart

We develop a computational framework for estimating simultaneously mechanical and electrical properties (current density and electrical activation time).; First, we present a method for estimating the mechanical properties of the in vivo heart using 2D MRI tissue-tagging and intra-ventricular pressure measurements. We propose a new physical model that accounts for possible regional variations using spatial basis functions defined over whole heart. We combine this globally defined model with a finite-element formulation and dynamic analysis, and estimate to the unknown parameters (basis-function coefficients). We evaluate the performance of the proposed estimator by computing the confidence region for the estimated parameters. Numerical examples demonstrate the applicability of our results. Next, we present an algorithm for estimating the current density of the heart using ECG/MCG sensor arrays. We introduce a spatio-temporal model of the current density which allows efficient estimation of the electrical parameters in the presence of spatially correlated noise. To solve the corresponding Fredholm equation we apply the element-free Galerkin method and derive the measurements as a function of the torso geometry and cardiac source. We also develop statistical signal processing techniques for estimating the current density when the time length of the heart cycle varies in time.; Finally, we present a new inverse electro-mechanical model based on the excitation-contraction coupling and dynamic analysis which includes inertial forces and moving mesh. The proposed model has significant potential for studying the coupling effects in the whole heart.