Robustness of Reduced Order Non-Parametric Model for Inverse ECG Solution Against Modeling and Measurement Noise

Abstract

Spline-based methods have been applied to inverse problems in science and engineering. Those studies have shown that if proper spline bases can be chosen, problem complexity can be significantly reduced while increasing estimation accuracy and robustness against the disturbances. We proposed non-parametric regression spline based approach for the solution of inverse ECG problem and assessed its robustness against measurement noise, variation of the heart size from its true size, and their combination. Our model defines the spline functions in terms of spatial coordinate variables based on the given epicardial surface geometry. The results demonstrated that, proposed method performed better than the Tikhonov regularization and can be feasible alternative for the inverse ECG problem.