Classification of iRBD and Parkinson's patients using a general data-driven sleep staging model built on EEG

Henriette Koch, Julie Anja Engelhard Christensen, Rune Frandsen, Lars Johan Arvastson, Søren Ro Christensen, Helge Bjarup Dissing Sørensen, Poul Jennum

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Sleep analysis is an important diagnostic tool for sleep disorders. However, the current manual sleep scoring is time-consuming as it is a crude discretization in time and stages. This study changes Esbroeck and Westover's [1] latent sleep staging model into a global model. The proposed data-driven method trained a topic mixture model on 10 control subjects and was applied on 10 other control subjects, 10 iRBD patients and 10 Parkinson's patients. In that way 30 topic mixture diagrams were obtained from which features reflecting distinct sleep architectures between control subjects and patients were extracted. Two features calculated on basis of two latent sleep states classified subjects as “control” or “patient” by a simple clustering algorithm. The mean sleep staging accuracy compared to classical AASM scoring was 72.4% for control subjects and a clustering of the derived features resulted in a sensitivity of 95% and a specificity of 80%. This study demonstrates that frequency analysis of sleep EEG can be used for data-driven global sleep classification and that topic features separates iRBD and Parkinson's patients from control subjects.
Original languageEnglish
Title of host publicationIEEE Engineering in medicine and biology society conference proceedings
PublisherIEEE
Publication date2013
Pages4275 - 4278
ISBN (Print)9781457702167
DOIs
Publication statusPublished - 2013
Event2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Oaska International Convention Center, Osaka, Japan
Duration: 3 Jul 20137 Jul 2013

Conference

Conference2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
LocationOaska International Convention Center
CountryJapan
CityOsaka
Period03/07/201307/07/2013

Keywords

  • diseases
  • electroencephalography
  • feature extraction
  • medical disorders
  • medical signal processing
  • pattern clustering
  • signal classification
  • sleep
  • Engineered Materials, Dielectrics and Plasmas

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