Intra-subject variability of snoring sounds in relation to body position, sleep stage, and blood oxygen level.
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 s...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 51; no. 4; pp. 429 - 440 |
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| Autores principales: | , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Apr2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104247034&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104247034 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Apr2013 vid: 51 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104247034 NLM23269579 2012034947 10.1007/s11517-012-1011-8 NLM23269579 104247034 ppf: 429 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Intra-subject variability of snoring sounds in relation to body position, sleep stage, and blood oxygen level. aug: au: Azarbarzin, Ali Moussavi, Zahra affil: Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB, R3T 5V6, Canada. sug: subj: Oxygen Blood Polysomnography Methods Posture Physiology Sleep Stages Physiology Snoring Physiopathology Adult Analysis of Variance Female Human Male Middle Age Factor Analysis ROC Curve Signal Processing, Computer Assisted Adult: 19-44 years Middle Aged: 45-64 years Female Male ab: 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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