RR interval analysis for detection of Atrial Fibrillation in ECG monitors.

We investigate two RR irregularity measures suitable for Atrial Fibrillation (AFIB) detection in ECG monitors, one based on the absolute deviation and the other based on the difference between successive RR intervals. A sequence of RR intervals is fed to the irregularity measures after applying certain constraints on length and beat classifications to provide criteria for detection of AFIB. Receiver Operating Curves (ROC) are used to analyze and compare the performance of the two methods against MIT-BIH Arrhythmia Database, MIT-BIH AFIB Database and a proprietary AFIB Database.

Methods of solving reduced lead systems for inverse electrocardiography.

In the context of inverse electrocardiography, we examine the problem of using measurements from sets of electrocardiographic leads that are smaller than the number of nodes in the associated geometric models of the torso. We compared several methods to estimate the solution from such reduced-lead measurements sets both with and without knowledge of prior statistics of the measurements. We present here simulation results that indicate that deleting rows of the forward matrix corresponding to the unmeasured leads performs best in the absence of prior statistics, and that Bayesian (or least-squares) estimation performs best in the presence of prior statistics.

Wavefront-based models for inverse electrocardiography.

We introduce two wavefront-based methods for the inverse problem of electrocardiography, which we term wavefront-based curve reconstruction (WBCR) and wavefront-based potential reconstruction (WBPR). In the WBCR approach, the epicardial activation wavefront is modeled as a curve evolving on the heart surface, with the evolution governed by factors derived phenomenologically from prior measured data. The body surface potential/wavefront relationship is modeled via an intermediate mapping of wavefront to epicardial potentials, again derived phenomenologically. In the WBPR approach, we iteratively construct an estimate of epicardial potentials from an estimated wavefront curve according to a simplified model and use it as an initial solution in a Tikhonov regularization scheme. Initial simulation results using measured canine epicardial data show considerable improvement in reconstructing activation wavefronts and epicardial potentials with respect to standard Tikhonov solutions. In particular the WBCR method accurately finds the anisotropic propagation early after epicardial pacing, and the WBPR method finds the wavefront (regions of sharp gradient of the potential) both accurately and with minimal smoothing.

A wavefront-based constraint for potential surface solutions in inverse electrocardiography.

Inverse electrocardiography in recent years has generally been approached using one of two quite distinct source models, either a potential-based approach or an activation-based approach. Each approach has advantages and disadvantages relative to the other, which are inherited by all specific methods based on a given approach. Recently our group has been working to develop models which can bridge between these two approaches, hoping to capture some of the most important advantages of both. In this work we present one such effort, which we term wavefront-based potential reconstruction (WBPR). It is a modification of standard regularization methods for potential-based inverse electrocardiography, into which we incorporate a constraint based on a wavefront-like approximation to the potential-based solution. Initial results indicate significant improvement with respect to localization and characterization of the wavefront in simulations using both epicardially and supra-ventricularly paced heartbeats.

Inverse electrocardiography in the framework of dynamic imaging problems.

We describe several current approaches which include temporal information into the inverse problem of electrocardiography. Some of these approaches operate directly on potential-based source models, and we show how three recent methods, introduced with rather distinct assumptions, can be placed in a common framework and compared. Others operate on parameterized models of the cardiac sources, and we discuss briefly how recent developments in curve evolution methods for inverse problems may allow more physiologically complex parametric models to be employed.