A review of automated sleep stage scoring based on physiological signals for the new millennia.

Journal: Computer methods and programs in biomedicine
Published Date:

Abstract

BACKGROUND AND OBJECTIVE: Sleep is an important part of our life. That importance is highlighted by the multitude of health problems which result from sleep disorders. Detecting these sleep disorders requires an accurate interpretation of physiological signals. Prerequisite for this interpretation is an understanding of the way in which sleep stage changes manifest themselves in the signal waveform. With that understanding it is possible to build automated sleep stage scoring systems. Apart from their practical relevance for automating sleep disorder diagnosis, these systems provide a good indication of the amount of sleep stage related information communicated by a specific physiological signal.

Authors

  • Oliver Faust
    Department of Engineering and Mathematics, Sheffield Hallam University, United Kingdom. Electronic address: o.faust@shu.ac.uk.
  • Hajar Razaghi
    Department of Engineering and Mathematics, Sheffield Hallam University, United Kingdom.
  • Ragab Barika
    Department of Engineering and Mathematics, Sheffield Hallam University, United Kingdom.
  • Edward J Ciaccio
    Department of Medicine, Celiac Disease Center, Columbia University, New York, USA.
  • U Rajendra Acharya
    School of Business (Information Systems), Faculty of Business, Education, Law & Arts, University of Southern Queensland, Darling Heights, Australia.