Literature DB >> 23269579

Intra-subject variability of snoring sounds in relation to body position, sleep stage, and blood oxygen level.

Ali Azarbarzin1, Zahra Moussavi.   

Abstract

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 blood oxygen level variations cause the snoring sounds to have different characteristics, and if it does how significant that effect would be. We extracted 12 characteristic features from snoring sound segments of 57 snorers and transformed them into a 4-D feature space using principal component analysis (PCA). Then, they were grouped based on the body position (side, supine, and prone), sleep stage (NREM, REM, and Arousal), and blood oxygen level (Normal and Desaturation). The probability density function of the transformed features was calculated for each class of categorical variables. The distance between the class-densities were calculated to determine which of these parameters affects the snoring sounds significantly. Analysis of Variance (ANOVA) was run for each categorical variable. The results show that the positional change has the highest effect on the snoring sounds; it results in forming distinct clusters of snoring sounds. Also, sleep state and blood oxygen level variation have been found to moderately affect the snoring sounds.

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Year:  2012        PMID: 23269579     DOI: 10.1007/s11517-012-1011-8

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  25 in total

1.  Analysis of snoring sound by psychoacoustic parameters.

Authors:  Michael Herzog; Thomas Bremert; Beatrice Herzog; Werner Hosemann; Holger Kaftan; Alexander Müller
Journal:  Eur Arch Otorhinolaryngol       Date:  2010-09-22       Impact factor: 2.503

2.  Automatic and unsupervised snore sound extraction from respiratory sound signals.

Authors:  Ali Azarbarzin; Zahra M K Moussavi
Journal:  IEEE Trans Biomed Eng       Date:  2010-07-29       Impact factor: 4.538

3.  Mixed-phase modeling in snore sound analysis.

Authors:  Udantha R Abeyratne; Asela S Karunajeewa; Craig Hukins
Journal:  Med Biol Eng Comput       Date:  2007-07-12       Impact factor: 2.602

Review 4.  The acoustics of snoring.

Authors:  Dirk Pevernagie; Ronald M Aarts; Micheline De Meyer
Journal:  Sleep Med Rev       Date:  2009-08-08       Impact factor: 11.609

5.  A comparison between recording sites of snoring sounds in relation to upper airway obstruction.

Authors:  Ali Azarbarzin; Zahra Moussavi
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2012

6.  Snoring sounds variability as a signature of obstructive sleep apnea.

Authors:  Ali Azarbarzin; Zahra Moussavi
Journal:  Med Eng Phys       Date:  2012-07-21       Impact factor: 2.242

7.  Multi-feature snore sound analysis in obstructive sleep apnea-hypopnea syndrome.

Authors:  Asela S Karunajeewa; Udantha R Abeyratne; Craig Hukins
Journal:  Physiol Meas       Date:  2010-11-30       Impact factor: 2.833

Review 8.  The upper airway in sleep: physiology of the pharynx.

Authors:  Indu Ayappa; David M Rapoport
Journal:  Sleep Med Rev       Date:  2003-02       Impact factor: 11.609

9.  Natural evolution of snoring: a 5-year follow-up study.

Authors:  K Martikainen; M Partinen; H Urponen; I Vuori; P Laippala; J Hasan
Journal:  Acta Neurol Scand       Date:  1994-12       Impact factor: 3.209

10.  Acoustic characteristics of snoring according to obstruction site determined by sleep videofluoroscopy.

Authors:  Tae-Bin Won; So Young Kim; Woo Hyun Lee; Doo Hee Han; Dong-Young Kim; Jeong-Whun Kim; Chae-Seo Rhee; Chul Hee Lee
Journal:  Acta Otolaryngol       Date:  2012-06       Impact factor: 1.494

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  5 in total

1.  Nasal pressure recordings for automatic snoring detection.

Authors:  Hyo-Ki Lee; Hojoong Kim; Kyoung-Joung Lee
Journal:  Med Biol Eng Comput       Date:  2015-09-21       Impact factor: 2.602

2.  Snore Sound Analysis Can Detect the Presence of Obstructive Sleep Apnea Specific to NREM or REM Sleep.

Authors:  Shahin Akhter; Udantha R Abeyratne; Vinayak Swarnkar; Craig Hukins
Journal:  J Clin Sleep Med       Date:  2018-06-15       Impact factor: 4.062

3.  Calculating annoyance: an option to proof efficacy in ENT treatment of snoring?

Authors:  René Fischer; Thomas S Kuehnel; Anne-Kathrin Merz; Tobias Ettl; Michael Herzog; Christian Rohrmeier
Journal:  Eur Arch Otorhinolaryngol       Date:  2016-06-22       Impact factor: 2.503

4.  Snoring: is a reliable assessment possible?

Authors:  René Fischer; Thomas S Kuehnel; Veronika Vielsmeier; Frank Haubner; Steffen Mueller; Christian Rohrmeier
Journal:  Eur Arch Otorhinolaryngol       Date:  2020-02-03       Impact factor: 2.503

5.  Are annoyance scores based on sound pressure levels suitable for snoring assessment in the home environment?

Authors:  René Fischer; Franziska Unverdorben; Thomas S Kuehnel; Veronika Vielsmeier; Gerrit Spanier; Steven C Marcrum; Christian Rohrmeier
Journal:  Sleep Breath       Date:  2020-05-27       Impact factor: 2.816

  5 in total

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