Sound-based sensing for snore signal analysis
Obstructive sleep apnea is a significant medical problem affecting up to 4 percent of middle-aged adults. The most common complaints are loud snoring with disrupted sleep and excessive daytime sleepiness and patients with apnea suffer from fragmented sleep and may develop cardiovascular abnormalitie...
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sg-ntu-dr.10356-494222023-07-07T17:12:01Z Sound-based sensing for snore signal analysis Chua, Wan Yi. Ser Wee School of Electrical and Electronic Engineering Centre for Signal Processing DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Obstructive sleep apnea is a significant medical problem affecting up to 4 percent of middle-aged adults. The most common complaints are loud snoring with disrupted sleep and excessive daytime sleepiness and patients with apnea suffer from fragmented sleep and may develop cardiovascular abnormalities because of the repetitive cycles of snoring, airway collapse and arousal.Snoring is the most common symptom and they are reported to contain vital information in the diagnosis of sleep disorders which relies on the expertise of the clinician that inspects whole night polysomnography (PSG) recordings. This inspection is time consuming and uncomfortable for the patient. However, evaluation of the success of these methods also relies on subjective criteria and the expertise of the clinician. Thus, there is a strong need for a tool to analyze the snore signals. Bachelor of Engineering 2012-05-18T06:30:29Z 2012-05-18T06:30:29Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/49422 en Nanyang Technological University 66 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Chua, Wan Yi. Sound-based sensing for snore signal analysis |
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Obstructive sleep apnea is a significant medical problem affecting up to 4 percent of middle-aged adults. The most common complaints are loud snoring with disrupted sleep and excessive daytime sleepiness and patients with apnea suffer from fragmented sleep and may develop cardiovascular abnormalities because of the repetitive cycles of snoring, airway collapse and arousal.Snoring is the most common symptom and they are reported to contain vital information in the diagnosis of sleep disorders which relies on the expertise of the clinician that inspects whole night polysomnography (PSG) recordings. This inspection is time consuming and uncomfortable for the patient. However, evaluation of the success of these methods also relies on subjective criteria and the expertise of the clinician. Thus, there is a strong need for a tool to analyze the snore signals. |
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Ser Wee |
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Ser Wee Chua, Wan Yi. |
format |
Final Year Project |
author |
Chua, Wan Yi. |
author_sort |
Chua, Wan Yi. |
title |
Sound-based sensing for snore signal analysis |
title_short |
Sound-based sensing for snore signal analysis |
title_full |
Sound-based sensing for snore signal analysis |
title_fullStr |
Sound-based sensing for snore signal analysis |
title_full_unstemmed |
Sound-based sensing for snore signal analysis |
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sound-based sensing for snore signal analysis |
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2012 |
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http://hdl.handle.net/10356/49422 |
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1772825755423604736 |