title: Characterising insomnia: A graph spectral theory approach.
abstract: This paper introduces a computational approach to characterise healthy controls and insomniacs based on graph spectral theory. Based upon expert-generated hypnograms of sleep onset periods, a network of sleep stages transitions is derived to compute four similarity distances amongst subjects' sleeping patterns. A subsequent statistical analysis is performed to differentiate the 16-subject healthy group from a 16-patient disordered cohort. Our findings demonstrated that the similarity distances based on eigenvalues determination, i.e. d1 and d4 were the most reliable and robust measures to characterise insomniacs, discriminating 93% and 87% of the affected population, respectively.
authors.forename: Ramiro
authors.initials: R
authors.lastname: Chaparro-Vargas
authors.forename: Beena
authors.initials: B
authors.lastname: Ahmed
authors.forename: Thomas
authors.initials: T
authors.lastname: Penzel
authors.forename: Dean
authors.initials: D
authors.lastname: Cvetkovic
mesh_terms: D016022:Case-Control Studies; D003196:Computer Graphics; D006801:Humans; D008954:Models, Biological; D017286:Polysomnography; D012890:Sleep / Q000502:physiology*; D007319:Sleep Initiation and Maintenance Disorders / Q000503:physiopathology*; D012894:Sleep Stages / Q000502:physiology