title: Methods of solving reduced lead systems for inverse electrocardiography.
abstract: 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.
authors.affiliation: Department of Algorithm Development, Draeger Medical, Andover, MA 01810, USA. alireza.ghodrati@draeger.com
authors.forename: Alireza
authors.initials: A
authors.lastname: Ghodrati
authors.forename: Dana H
authors.initials: DH
authors.lastname: Brooks
authors.forename: Robert S
authors.initials: RS
authors.lastname: MacLeod
mesh_terms: D000465:Algorithms; D018780:Body Surface Potential Mapping / Q000379:methods*; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006329:Heart Conduction System / Q000503:physiopathology*; D006801:Humans; D008955:Models, Cardiovascular