title: Arrhythmia discrimination in implantable cardioverter defibrillators using support vector machines applied to a new representation of electrograms.
abstract: Arrhythmia classification remains a major challenge for appropriate therapy delivery in implantable cardioverter defibrillators (ICDs). The purpose of this paper is to present a new algorithm for arrhythmia discrimination based on a statistical classification by support vector machines of a novel 2-D representation of electrograms (EGMs) named spatial projection of tachycardia (SPOT) EGMs. SPOT-based discrimination algorithm provided sensitivity and specificity of 98.8% and 91.3%, respectively, on a test database. A simplified version of the algorithm is also presented, which can be directly implemented in the ICD.
authors.affiliation: Department of Advanced Clinical Research, Sorin CRM, 92143 Clamart, France. paola.milpied@sorin.com
authors.forename: Paola
authors.initials: P
authors.lastname: Milpied
authors.forename: Rémi
authors.initials: R
authors.lastname: Dubois
authors.forename: Pierre
authors.initials: P
authors.lastname: Roussel
authors.forename: Christine
authors.initials: C
authors.lastname: Henry
authors.forename: Gérard
authors.initials: G
authors.lastname: Dreyfus
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001185:Artificial Intelligence; D017147:Defibrillators, Implantable; D022062:Electrophysiologic Techniques, Cardiac / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012815:Signal Processing, Computer-Assisted; D013610:Tachycardia / Q000145:classification* / Q000175:diagnosis