title: Real-time sleep quality assessment using single-lead ECG and multi-stage SVM classifier.
abstract: Sleep efficiency measures provide an objective assessment to gauge the quality of individual's sleep. In this study we present a home-based, automated and non-intrusive system that is based on Electrocardiogram (ECG) measurements and uses a multi-stage Support Vector Machines (SVM) classifier to measure three indices for sleep quality assessment per 30 s epoch segment: Sleep Efficiency Index, Delta-Sleep Efficiency Index and Sleep Onset Latency. This method provides an alternative to the intrusive and expensive Polysomnography (PSG) and scoring by Rechtschaffen and Kales visual method.
authors.affiliation: Alcatel-Lucent, Plano, TX 75075, USA. majdi@ieee.org
authors.forename: Majdi
authors.initials: M
authors.lastname: Bsoul
authors.forename: Hlaing
authors.initials: H
authors.lastname: Minn
authors.forename: Mehrdad
authors.initials: M
authors.lastname: Nourani
authors.forename: Gopal
authors.initials: G
authors.lastname: Gupta
authors.forename: Lakshman
authors.initials: L
authors.lastname: Tamil
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003199:Computer Systems; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012894:Sleep Stages / Q000502:physiology*