DocumentCode :
2097807
Title :
Sleep-quality assessment from full night audio recordings of sleep apnea patients
Author :
Dafna, E. ; Tarasiuk, A. ; Zigel, Y.
Author_Institution :
Dept. of Biomed. Eng., Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel
fYear :
2012
fDate :
Aug. 28 2012-Sept. 1 2012
Firstpage :
3660
Lastpage :
3663
Abstract :
In this work, a novel system (method) for sleep quality analysis is proposed. Its purpose is to assist an alternative non-contact method for detecting and diagnosing sleep related disorders based on acoustic signal processing. In this work, audio signals of 145 patients with obstructive sleep apnea were recorded (more than 1000 hours) in a sleep laboratory and analyzed. The method is based on the assumption that during sleep the respiratory efforts are more periodically patterned and consistent relative to a waking state; furthermore, the sound intensity of those efforts is higher, making the pattern more noticeable relative to the background noise level. The system was trained on 50 subjects and validated on 95 subjects. The system accuracy for detecting sleep/wake state is 82.1% (epoch by epoch), resulting in 3.9% error (difference) in detecting sleep latency, 11.4% error in estimating total sleep time, and 11.4% error in estimating sleep efficiency.
Keywords :
acoustic signal processing; audio signal processing; electroencephalography; medical disorders; medical signal processing; neurophysiology; pneumodynamics; signal denoising; sleep; acoustic signal processing; alternative noncontact method; audio signals; background noise level; detecting sleep-wake state; full night audio recordings; obstructive sleep apnea; respiratory efforts; sleep apnea patients; sleep latency; sleep quality analysis; sleep related disorder detection; sleep related disorder diagnosis; sleep-quality assessment; sound intensity; waking state; Artificial intelligence; Estimation; Feature extraction; Hidden Markov models; Sleep apnea; Vectors; Audio Signal Processing; Obstructive Sleep Apnea; Sleep Quality Estimation; Snore Detection; Aged; Aged, 80 and over; Female; Humans; Male; Middle Aged; Polysomnography; Reproducibility of Results; Respiratory Sounds; Sleep; Sleep Apnea, Obstructive; Tape Recording;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
ISSN :
1557-170X
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/EMBC.2012.6346760
Filename :
6346760
Link To Document :
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