Development of OSA Event Detection Using Threshold Based Automatic Classification
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Authors
Almazaydeh, Laiali
Elleithy, Khaled M.
Pande, Varun
Faezipour, Miad
Issue Date
2012-11-14
Type
Article
Language
en_US
Keywords
Sleep apnea , Polysomnography (PSG) , Respiratory signal , Video monitoring
Alternative Title
Abstract
Obstructive Sleep Apnea (OSA) is a very serious sleeping disorder resulting in the temporary blockage of the airflow airway that can be deadly if left untreated. OSA is not a rare condition; in the US, from 18 to 50 million people, most of them remain undiagnosed due to cost, cumbersome and resource limitations of overnight polysomnography (PSG) at sleep labs. Instead, automated, at-home devices that patients can simply use while asleep seem to be very attractive and highly on-demand. This paper presents a method for OSA screening and user notification based on the respiratory recording and video monitoring as a secondary system during sleep in order to alert of the apnea event and help patient to recover.
Description
Citation
Publisher
International Society for Computers and Their Applications, Inc.