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Proceedings Paper

Respiratory sound recordings for detection of sleep apnea
Author(s): Karina E. Waldemark; Kenneth I. Agehed; Thomas Lindblad
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Paper Abstract

Sleep apnea is characterized by frequent prolonged interruptions of breathing during sleep. This syndrome causes severe sleep disorders and is often responsible for development of other diseases such as heart problems, high blood pressure and daytime fatigue, etc. After diagnosis, sleep apnea is often successfully treated by applying positive air pressure (CPAP) to the mouth and nose. Although effective, the (CPAP) equipment takes up a lot of space and the connected mask causes a lot of inconvenience for the patients. This raised interest in developing new techniques for treatment of sleep apnea syndrome. Several studies indicated that electrical stimulation of the hypoglossal nerve and muscle in the tongue may be a useful method for treating patients with severe sleep apnea. In order to be able to successfully prevent the occurrence of apnea it is necessary to have some technique for early and fast on-line detection or prediction of the apnea events. This paper suggests using measurements of respiratory airflow (mouth temperature). The signal processing for this task includes the use of a window short-FFT technique and uses an artificial back propagation neural net to model or predict the occurrence of apneas. The results show that early detection of respiratory interruption is possible and that the delay time for this is small.

Paper Details

Date Published: 22 March 1999
PDF: 24 pages
Proc. SPIE 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks, (22 March 1999);
Show Author Affiliations
Karina E. Waldemark, Royal Institute of Technology (Sweden)
Kenneth I. Agehed, Royal Institute of Technology (Sweden)
Thomas Lindblad, Royal Institute of Technology (Sweden)

Published in SPIE Proceedings Vol. 3728:
Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks
Thomas Lindblad; Mary Lou Padgett; Jason M. Kinser, Editor(s)

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