title: Detection of K-complexes and sleep spindles (DETOKS) using sparse optimization.
abstract: BACKGROUND
  This paper addresses the problem of detecting sleep spindles and K-complexes in human sleep EEG. Sleep spindles and K-complexes aid in classifying stage 2 NREM human sleep.
  
  
  METHODS
  We propose a non-linear model for the EEG, consisting of a transient, low-frequency, and an oscillatory component. The transient component captures the non-oscillatory transients in the EEG. The oscillatory component admits a sparse time-frequency representation. Using a convex objective function, this paper presents a fast non-linear optimization algorithm to estimate the components in the proposed signal model. The low-frequency and oscillatory components are used to detect K-complexes and sleep spindles respectively.
  The performance of the proposed method is evaluated using an online EEG database. The F1 scores for the spindle detection averaged 0.70 ± 0.03 and the F1 scores for the K-complex detection averaged 0.57 ± 0.02. The Matthews Correlation Coefficient and Cohen's Kappa values were in a range similar to the F1 scores for both the sleep spindle and K-complex detection. The F1 scores for the proposed method are higher than existing detection algorithms.
  
  
  CONCLUSIONS
  Comparable run-times and better detection results than traditional detection algorithms suggests that the proposed method is promising for the practical detection of sleep spindles and K-complexes.
authors.affiliation: Department of Mathematics, School of Engineering, New York University, USA. Electronic address: ankit.parekh@nyu.edu.
authors.forename: Ankit
authors.initials: A
authors.lastname: Parekh
authors.affiliation: Department of Electrical and Computer Engineering, School of Engineering, New York University, USA.
authors.forename: Ivan W
authors.initials: IW
authors.lastname: Selesnick
authors.affiliation: Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, School of Medicine, New York University, USA.
authors.forename: David M
authors.initials: DM
authors.lastname: Rapoport
authors.affiliation: Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, School of Medicine, New York University, USA.
authors.forename: Indu
authors.initials: I
authors.lastname: Ayappa
mesh_terms: D000465:Algorithms; D000818:Animals; D058256:Brain Waves / Q000502:physiology*; D004569:Electroencephalography; D006801:Humans; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated; D012890:Sleep / Q000502:physiology*
keywords: Convex optimization; K-complex detection; Sleep spindle detection; Sparse signal