title: Insomnia Characterization: From Hypnogram to Graph Spectral Theory.
abstract: To quantify and differentiate control and insomnia sleep onset patterns through biomedical signal processing of overnight polysomnograms.
  
  
  
  The approach consisted of three tandem modules: 1) biosignal processing module, which used state-space time-varying autoregressive moving average (TVARMA) processes with recursive particle filter, 2) hypnogram generation module that implemented a fuzzy inference system (FIS), and 3) insomnia characterization module that discriminated between control and subjects with insomnia using a logistic regression model trained with a set of similarity measures ( d1, d2 , d3, d4). The study employed sleep onset periods from 16 control and 16 subjects with insomnia.
  
  
  
  State-spaced TVARMA processes with recursive particle filtering provided resilience to nonlinear, nonstationary, and non-Gaussian conditions of biosignals. FIS managed automated sleep scoring robust to intersubjects' and interraters' variability. The similarity distances quantified in a scalar measure the transitions amongst sleep onset stages, computed from expert and automated hypnograms. A statistical set of unpaired two-tailed t -tests suggested that distances d1 , d2, and d3 had larger statistical significance ( ) to characterize sleeping patterns. The logistic regression model classified control and subjects with insomnia with sensitivity 87 % , specificity 75 %, and accuracy 81 %.
  
  
  
  Our approach can perform a supportive role in either biosignal processing, sleep staging, insomnia characterization, or all the previous, coping with time-consuming procedures and massive data volumes of standard protocols.
  
  
  
  The introduction of graph spectral theory and logistic regression for the diagnosis of insomnia represents a novel concept, attempting to describe complex sleep dynamics throughout transitions networks and scalar measures.
authors.forename: Ramiro
authors.initials: R
authors.lastname: Chaparro-Vargas
authors.forename: Beena
authors.initials: B
authors.lastname: Ahmed
authors.forename: Niels
authors.initials: N
authors.lastname: Wessel
authors.forename: Thomas
authors.initials: T
authors.lastname: Penzel
authors.forename: Dean
authors.initials: D
authors.lastname: Cvetkovic
mesh_terms: D017143:Fuzzy Logic; D006801:Humans; D016015:Logistic Models; D017286:Polysomnography / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D012890:Sleep / Q000502:physiology*; D007319:Sleep Initiation and Maintenance Disorders / Q000175:diagnosis* / Q000503:physiopathology*