Cart (Loading....) | Create Account
Close category search window

Sleep apnea detection using flow spectral analysis and fuzzy logic

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Haja, T. ; Dept. of Biomed. Eng., Texas Univ., Arlington, TX, USA ; Behbehani, K. ; Yen, F.C. ; Lucas, E.A.
more authors

Diagnosis of sleep apnea is currently performed by a full night polysomnography study at sleep laboratories. The majority of apnea patients are then treated by constant positive airway pressure (CPAP) device. A new algorithm to detect and classify apnea that could be easily incorporated into CPAP was developed. The study used data from ten subjects (6 males, 4 females, age mean (SD): 52 (13), BMI mean (SD): 34 (8)) who were previously diagnosed with sleep apnea. The CPAP flow data was used for the algorithm development. Spectral analysis of data was performed and area, weighted mean frequency and amplitude were determined. These were fed as inputs to a fuzzy logic program, which was used to detect normal, obstructive sleep apnea (OSA) and central sleep apnea (CSA). The data analyzed included 591 normal breaths and 306 apnea events (165 obstructive and 140 central). Of these 299 normal breaths and 148 apnea events (77 obstructive and 71 central) were used for algorithm development and the remainder for testing. The algorithm had correct detection rates of 99.6% for normal breaths, 69.6% for CSA and 71.9% for OSA. The results suggest that the algorithm could be successfully used to determine if a subject had apnea or not. It has limited success in differentiating apnea types

Published in:

[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint  (Volume:1 )

Date of Conference:


Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.