NDLI: A noninvasive technique for detecting obstructive and central sleep apnea

Content Provider	IEEE Xplore Digital Library
Author	Fu-Chung Yen Behbehani, K. Lucas, E.A. Burk, J.R. Axe, J.R.
Copyright Year	1964
Abstract	A new noninvasive method to detect obstructive and central sleep apnea [(OSA) and (CSA)] events is described. Data were collected from ten volunteer subjects with a previous diagnosis of OSA while they were titrated for continuous positive airway pressure (CPAP) therapy. Apneic events were identify by analyzing of estimated airway impedance determined from pressure and airflow signals delivered from CPAP. To enhance performance of this technique, a single-frequency (5 Hz with 0.5 cmH/sub 2/O peak-to-peak amplitude) probing signal was superimposed on the applied CPAP pressure. The results indicated that estimated airway impedance during OSA (mean: 17.9, SD: 3.4, N=50) was significantly higher then during CSA (mean: 4.1, SD: 1.7, N=50). When the estimated impedance of OSA and CSA events were compared to a fixed threshold, 100% of all events can be correctly categorized. These results indicate that it may be possible to diagnose OSA and CSA noninvasively based upon this technique. The instrument and the algorithm required are relatively simple and can be incorporated in a home-based device. If this method was used for prescreening apnea patients, it could reduce cost, waiting time, and discomfort associated with traditional diagnostic procedures.
Sponsorship	IEEE Engineering in Medicine and Biology Society
Page Count	7
File Size	162646
Starting Page	1262
Ending Page	1268
File Format	PDF
ISSN	00189294
Volume Number	44
Issue Number	12
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-12-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sleep apnea Impedance Esophagus Medical treatment Biomedical engineering Electromyography Biomedical measurements Surgery Event detection Signal analysis
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering

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