title: Detection of sleep apnea from surface ECG based on features extracted by an autoregressive model.
abstract: This study proposes an alternative evaluation of Obstructive Sleep Apnea (OSA) based on ECG signal during sleep time. OSA is a common sleep disorder produced by repetitive occlusions in the upper airways. This respiratory disturbance produces a specific pattern on ECG. Extraction of ECG characteristics, as Heart Rate Variability (HRV) and peak R area, offers alternative measures for a sleep apnea pre-diagnosis. 50 recordings coming from the apnea Physionet database were used in the analysis, this database is part of the 70 recordings used for the Computer in Cardiology challenge celebrated in 2000. A bivariate autoregressive model was used to evaluate beat-by-beat power spectral density of HRV and R peak area. K-Nearest Neighbor (KNN) supervised learning classifier was employed for categorizing apnea events from normal ones, on a minute-by-minute basis for each recording. Data were split into two sets, training and testing set, each one with 25 recordings. The classification results showed an accuracy higher than 85% in both training and testing. In addition it was possible to separate completely between Apnea and Normal subjects and almost completely among Apnea, Normal and Borderline subjects.
authors.affiliation: Dept. of Biomedical Engineering, Politecnico di Milano, Pzza. Leonardo da Vinci 32, Italy. martin.mendez@polimi.it
authors.forename: Martin O
authors.initials: MO
authors.lastname: Mendez
authors.forename: Davide D
authors.initials: DD
authors.lastname: Ruini
authors.forename: Omar P
authors.initials: OP
authors.lastname: Villantieri
authors.forename: Matteo
authors.initials: M
authors.lastname: Matteucci
authors.forename: Thomas
authors.initials: T
authors.lastname: Penzel
authors.forename: Sergio
authors.initials: S
authors.lastname: Cerutti
authors.forename: Anna M
authors.initials: AM
authors.lastname: Bianchi
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D005103:Expert Systems; D005260:Female; D006339:Heart Rate; D006801:Humans; D008297:Male; D008959:Models, Neurological; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods; D012044:Regression Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012891:Sleep Apnea Syndromes / Q000175:diagnosis* / Q000503:physiopathology*