• DocumentCode
    2474708
  • Title

    Automatic sleep spindles detection — Overview and development of a standard proposal assessment method

  • Author

    Devuyst, S. ; Dutoit, T. ; Stenuit, P. ; Kerkhofs, M.

  • Author_Institution
    TCTS Lab., Univ. de Mons - UMONS, Mons, Belgium
  • fYear
    2011
  • fDate
    Aug. 30 2011-Sept. 3 2011
  • Firstpage
    1713
  • Lastpage
    1716
  • Abstract
    Since the 1970s, various automatic sleep spindles procedures have been implemented and presented in the literature. Unfortunately, their results are not easily comparable because the databases, the assessment methods and the terminologies employed are often radically different. In this study, we propose a systematic assessment method for any automatic sleep spindles detection algorithm. We apply this assessment method to our own automatic detection process in order to illustrate and legitimate its use. We obtain a global sensitivity of 70.20%, for a false positive proportion (relative to the total number of visually scored sleep spindles) of only 26.44% (False positive rate= 1.38% and specificity = 98.62%).
  • Keywords
    electroencephalography; medical signal detection; sleep; EEG; automatic sleep spindle detection; false positive rate; global sensitivity; standard proposal assessment method; Band pass filters; Detection algorithms; Electroencephalography; Electromyography; Sensitivity; Sleep; Visualization; Adult; Algorithms; Brain; Diagnosis, Computer-Assisted; Electroencephalography; Female; Humans; Male; Middle Aged; Pattern Recognition, Automated; Polysomnography; Reproducibility of Results; Sensitivity and Specificity; Sleep; Sleep Disorders;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
  • Conference_Location
    Boston, MA
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4121-1
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2011.6090491
  • Filename
    6090491