title: On improvement of detection of Obstructive Sleep Apnea by partial least square-based extraction of dynamic features.
abstract: This paper presents a methodology for Obstructive Sleep Apnea (OSA) detection based on the HRV analysis, where as a measure of relevance PLS is used. Besides, two different combining approaches for the selection of the best set of contours are studied. Attained results can be oriented in research focused on finding alternative methods minimizing the HRV-derived parameters used for OSA diagnosing, with a diagnostic accuracy comparable to a polysomnogram. For two classes (normal, apnea) the results for PLS are: specificity 90%, sensibility 91% and accuracy 93.56%.
authors.affiliation: Control and Digital Signal Processing Group, Universidad Nacional de Colombia, sede Manizales, Colombia. lmsepulvedac@unal.edu.co
authors.forename: L M
authors.initials: LM
authors.lastname: Sepulveda-Cano
authors.forename: C M
authors.initials: CM
authors.lastname: Travieso-Gonzalez
authors.forename: J I
authors.initials: JI
authors.lastname: Godino-Llorente
authors.forename: G
authors.initials: G
authors.lastname: Castellanos-Dominguez
mesh_terms: D000465:Algorithms; D004562:Electrocardiography / Q000379:methods; D006339:Heart Rate / Q000502:physiology*; D016018:Least-Squares Analysis; D012815:Signal Processing, Computer-Assisted; D020181:Sleep Apnea, Obstructive / Q000175:diagnosis* / Q000503:physiopathology