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In this paper, an automatic and unsupervised snore detection algorithm is proposed. The respiratory sound signals of 30 patients with different levels of airway obstruction were recorded by two microphones: one placed over the trachea (the tracheal microphone), and the other was a freestanding microphone (the ambient microphone). All the recordings were(More)
Snoring sounds vary significantly within and between snorers. In this study, the variation of snoring sounds and its association with obstructive sleep apnea (OSA) are quantified. Snoring sounds of 42 snorers with different degrees of obstructive sleep apnea and 15 non-OSA snorers were analyzed. The sounds were recorded by a microphone placed over the(More)
In a multidimensional feature space, the snoring sounds can extend from a very compact cluster to highly distinct clusters. In this study, we investigated the cause of snoring sound’s variation within the snorers. It is known that a change in body position and sleep stage can affect snoring during sleep but it is unclear whether positional, sleep state, and(More)
This paper presents the results of our study on investigating the acoustical properties of snoring sounds (SS) recorded by two microphones (one over trachea and one hung in the air within 30-50 cm away from the subject) in relation to sleep apnea. Several features were extracted from SS segments of 50 snorers with different Apnea-Hypopnea Index (AHI). We(More)
In this study, an automatic and online snore detection algorithm is proposed. The respiratory sound signals were recorded simultaneously with Polysomnography (PSG) data during sleep from 20 patients (10 simple snorers and 10 OSA patients). The sound signals were recorded by two tracheal and ambient microphones. The potential snoring episodes were identified(More)
Tracheal respiratory sound analysis is a simple and non-invasive way to study the pathophysiology of the upper airway and has recently been used for acoustic estimation of respiratory flow and sleep apnea diagnosis. However in none of the previous studies was the respiratory flow–sound relationship studied in people with obstructive sleep apnea (OSA), nor(More)
In this paper, the Gaussianity and linearity of the snoring sound (SS) segments extracted from respiratory sounds are discussed. The respiratory sound signals were recorded from 30 individuals by two microphones simultaneously with full-night Polysomnography (PSG) during sleep. The first microphone was placed over the trachea (the tracheal microphone), and(More)
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Tracheal respiratory sound analysis is a simple and non-invasive way to study the pathophysiology of the upper airways; it has recently been used for acoustical flow estimation and sleep apnea diagnosis. However in none of the previous studies, the accuracy of acoustical flow estimation was investigated neither during sleep nor in people with obstructive(More)
Obstructive sleep apnea (OSA) is a prevalent disorder. The accepted method of diagnosis in widespread clinical practice, polysomnography (PSG), is costly and very time consuming; therefore, quick screening methods, especially when there is a need for quick diagnosis, is of great interest. Diagnostic methods which exploit subtle differences in breath sounds(More)
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