Automatic Classification of Sleep/Wake Stages Using Two-Step System

  • Lukáš Zoubek
  • Florian Chapotot
Conference paper

DOI: 10.1007/978-3-642-22389-1_10

Part of the Communications in Computer and Information Science book series (CCIS, volume 188)
Cite this paper as:
Zoubek L., Chapotot F. (2011) Automatic Classification of Sleep/Wake Stages Using Two-Step System. In: Snasel V., Platos J., El-Qawasmeh E. (eds) Digital Information Processing and Communications. Communications in Computer and Information Science, vol 188. Springer, Berlin, Heidelberg

Abstract

This paper presents application of an automatic classification system on 53 animal polysomnographic recordings. A two-step automatic system is used to score the recordings into three traditional stages: wake, NREM sleep and REM sleep. In the first step of the analysis, monitored signals are analyzed using artifact identification strategy and artifact-free signals are selected. Then, 30sec epochs are classified according to relevant features extracted from available signals using artificial neural networks. The overall classification accuracy reached by the presented classification system exceeded 95%, when analyzed 53 polysomnographic recordings.

Keywords

decision making diagnosis medical applications pattern recognition signal processing 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Lukáš Zoubek
    • 1
  • Florian Chapotot
    • 2
  1. 1.Department of Information and Communication TechnologiesUniversity of OstravaOstravaCzech Republic
  2. 2.Department of MedicineThe University of ChicagoChicagoUSA

Personalised recommendations