DocumentCode :
667336
Title :
On the use of smartphones for detecting obstructive sleep apnea
Author :
Al-Mardini, Mamoun ; Aloul, Fadi ; Sagahyroon, Assim ; Al-Husseini, Luai
Author_Institution :
American Univ. of Sharjah, Sharjah, United Arab Emirates
fYear :
2013
fDate :
10-13 Nov. 2013
Firstpage :
1
Lastpage :
4
Abstract :
Obstructive Sleep Apnea (OSA) is a common sleep disorder which is characterized by recurrent blockage of the upper airway, often resulting in oxygen desaturation. Attended overnight polysomnography (PSG) has been recommended as the golden standard for the diagnostic of OSA at hospitals, which requires an expensive attended overnight stay at a hospital with considerable wiring between the PSG device and the human body. In this work, we implement a reliable, comfortable, inexpensive, and easily available portable device that allows users to apply the OSA test at home without the need for attended overnight tests. The design takes advantage of a smartphone´s built-in sensors, pervasiveness, computational capabilities, and user-friendly interface to screen OSA. We extract three main physiological signals to diagnose OSA which are (1) oxygen saturation using an external oximeter, (2) respiratory effort using the smartphone´s built-in microphone, and (3) body movement using the smartphone´s built-in accelerometer. The signals are analyzed on the smartphone to screen the OSA. Finally, we examine our system´s ability to screen the disease as compared to the golden standard by testing it on 15 subjects. Results show that 100% of the sick subjects were correctly classified as having OSA, and 85.7% of the healthy subjects were correctly classified as not having OSA. These preliminary results demonstrate the effectiveness of the proposed system when compared to the golden standard and emphasize the important role of smartphones in healthcare.
Keywords :
accelerometers; medical disorders; medical signal processing; microphones; oximetry; patient diagnosis; sleep; smart phones; OSA test; PSG device; attended overnight polysomnography; body movement; disease; external oximeter; healthcare; hospital; obstructive sleep apnea detection; oxygen desaturation; physiological signals; respiratory effort; sleep disorder; smartphone built-in accelerometer; smartphone built-in microphone; upper airway recurrent blockage; Accelerometers; Biomedical monitoring; Diseases; Physiology; Sleep apnea; Smart phones; Standards;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Bioengineering (BIBE), 2013 IEEE 13th International Conference on
Conference_Location :
Chania
Type :
conf
DOI :
10.1109/BIBE.2013.6701674
Filename :
6701674
Link To Document :
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