Detection of K-complexes based on the wavelet transform

Lærke K. Krohne, Rie B. Hansen, Julie Anja Engelhard Christensen, Helge Bjarup Dissing Sørensen, Poul Jennum

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

Abstract

Sleep scoring needs computational assistance to reduce execution time and to assure high quality. In this pilot study a semi-automatic K-Complex detection algorithm was developed using wavelet transformation to identify pseudo-K-Complexes and various feature thresholds to reject false positives. The algorithm was trained and tested on sleep EEG from two databases to enhance its general applicability. When testing on data from subjects from the DREAMS© database, a mean true positive rate of 74 % and a positive predictive value of 65 % were achieved. After adjusting a few thresholds to adapt to the second database, the Danish Center for Sleep Medicine, a similar performance was achieved. The algorithm performs at the level of the State of the Art and surpasses the inter-rater agreement rate.
Original languageEnglish
Title of host publication2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
PublisherIEEE
Publication date2014
Pages5450-5453
ISBN (Print)978-1-4244-7929-0
DOIs
Publication statusPublished - 2014
Event36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Chicago, IL, United States
Duration: 26 Aug 201430 Aug 2014
Conference number: 36
http://embc.embs.org/2014/

Conference

Conference36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Number36
CountryUnited States
CityChicago, IL
Period26/08/201430/08/2014
Internet address

Keywords

  • Bioengineering
  • Databases
  • Electroencephalography
  • Feature extraction
  • Prediction algorithms
  • Sleep
  • Visualization
  • Wavelet transforms

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