Automated system for analyzing sleep

Isaac N. Bankman, Robert A. Wise, Norman M. Schubert, Xiao N. Yuan, Alan R. Schwartz, Philip L. Smith

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An automated system that emulates the visual analysis of sleep records (electroencephalograms, electrooculograms, and electromyograms) by depicting relevant waveforms (features) and evaluating the sleep stage according to the standard scoring manual is presented. Algorithms for detection of K-complexes, spindles, rapid eye movements, electromyographic bursts, delta, alpha, and mixed frequency waveforms based on morphological parameters that reflect visual recognition, perform in the 91 to 98% correct range. The staging algorithms that were developed use logic structures that emulate human decision-making. The somnogram obtained on the first full-night (eight-hour) sleep record that was analyzed is in 92% agreement with the somnogram provided by an experienced sleep clinician. The automated system detects all the features online and completes the staging in 5 min offline.

Original languageEnglish (US)
Title of host publicationProceedings of the Annual Conference on Engineering in Medicine and Biology
PublisherPubl by IEEE
Pages1315-1316
Number of pages2
Editionpt 3
ISBN (Print)0780302168
StatePublished - Dec 1 1991
EventProceedings of the 13th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Orlando, FL, USA
Duration: Oct 31 1991Nov 3 1991

Publication series

NameProceedings of the Annual Conference on Engineering in Medicine and Biology
Numberpt 3
Volume13
ISSN (Print)0589-1019

Other

OtherProceedings of the 13th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
CityOrlando, FL, USA
Period10/31/9111/3/91

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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