• DocumentCode
    471998
  • Title

    Dynamic Data Analysis in Obstructive Sleep Apnea

  • Author

    Karunajeewa, Asela S. ; Abeyratne, Udantha R. ; Rathnayake, Suren I. ; Swarnkar, Vinayak

  • Author_Institution
    Sch. of Inf. Technol. & Electr. Eng., Queensland Univ., Brisbane, Qld.
  • fYear
    2006
  • fDate
    Aug. 30 2006-Sept. 3 2006
  • Firstpage
    4510
  • Lastpage
    4513
  • Abstract
    Obstructive Sleep Apnea (OSA) is a serious disease caused by the collapse of upper airways during sleep. The present method of measuring the severity of OSA is the Apnea Hypopnea Index (AHI). The AHI is defined as the average number of Obstructive events (Apnea and Hypopnea, OAH-events) during the total sleep period. The number of occurrence of OAH events during each hour of sleep is a random variable with an unknown probability density function. Thus the measure AHI alone is insufficient to describe its true nature. We propose a new measure Dynamic Apnea Hypopnea Index Time Series (DAHI), which captures the temporal density of Apnea event over shorter time intervals, and use its higher moments to obtain a dynamic characterization of OSA
  • Keywords
    diseases; neurophysiology; probability; sleep; time series; OSA; disease; dynamic apnea hypopnea index time series; dynamic data analysis; obstructive sleep apnea; probability density function; temporal density; upper airway collapse; Cities and towns; Data analysis; Diseases; Fatigue; Histograms; Probability density function; Random variables; Sleep apnea; Time measurement; USA Councils;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
  • Conference_Location
    New York, NY
  • ISSN
    1557-170X
  • Print_ISBN
    1-4244-0032-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2006.260203
  • Filename
    4462804