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
Link To Document :
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