title: Automated polysomnogram artifact compensation using the generalized singular value decomposition algorithm.
abstract: Manual/visual polysomnogram (psg) analysis is a standard and commonly implemented procedure utilized in the diagnosis and treatment of sleep related human pathologies. Current technological trends in psg analysis focus upon translating manual psg analysis into automated/computerized approaches. A necessary first step in establishing efficient automated human sleep analysis systems is the development of reliable pre-processing tools to discriminate between outlier/artifact instances and data of interest. This paper investigates the application of an automated approach, using the generalized singular value decomposition algorithm, to compensate for specific psg artifacts.
authors.affiliation: NINDS postdoctoral fellow at Emory University School of Medicine Department of Neurology, Atlanta, GA 30322, USA. jafairl@emory.edu
authors.forename: Jacqueline
authors.initials: J
authors.lastname: Fairley
authors.forename: Ashley N
authors.initials: AN
authors.lastname: Johnson
authors.forename: George
authors.initials: G
authors.lastname: Georgoulas
authors.forename: George
authors.initials: G
authors.lastname: Vachtsevanos
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001330:Electronic Data Processing / Q000379:methods*; D006801:Humans; D017286:Polysomnography / Q000295:instrumentation*; D013997:Time Factors