title: Lead selection: old and new methods for locating the most electrocardiogram information.
abstract: The present article summarizes the work presented in several key studies over the past 3 decades in the area of limited lead selection. Specifically, we summarize the pioneering research of those investigators searching for the most "signal" information and those searching for the most "diagnostic" information. Initially, we present the work conducted by Barr et al and, later, Lux et al who investigated body surface potential maps to locate those recording sites containing the most signal information that subsequently facilitated the estimation of the electrical potentials at all other areas of the thoracic surface. Subsequently, the discussion focuses on the early work conducted by Kornreich et al, who used statistical methods to identify those recording sites containing optimal measurement features to improve upon the identification of different disease types. In addition to the aforementioned work, an overview of more recent complementary work is summarized.
authors.affiliation: School of Computing and Mathematics, Computer Science Research Institute, University of Ulster, Northern Ireland. mp.donnelly@ulster.ac.uk
authors.forename: Mark P
authors.initials: MP
authors.lastname: Donnelly
authors.forename: Dewar D
authors.initials: DD
authors.lastname: Finlay
authors.forename: Chris D
authors.initials: CD
authors.lastname: Nugent
authors.forename: Norman D
authors.initials: ND
authors.lastname: Black
mesh_terms: D000465:Algorithms; D018780:Body Surface Potential Mapping / Q000295:instrumentation* / Q000379:methods*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000295:instrumentation* / Q000379:methods*; D004566:Electrodes; D006801:Humans; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity