Literature DB >> 9493925

Intensity pattern of snoring sounds as a predictor for sleep-disordered breathing.

D L Van Brunt1, K L Lichstein, S L Noe, R N Aguillard, K W Lester.   

Abstract

The relationship between a new operational definition of sleep sounds and apnea was examined in a population of 69 patients referred for overnight evaluations in a sleep disorders center. The sample contained 18 women (mean age 53.6 years) and 51 men (mean age 48.4 years). Subjects underwent polysomnography (PSG) with concurrent graphical recording of sleep sound intensities throughout the night. An acoustical signature event (ASE) was defined as a loud sound preceded by at least 10 but no more than 90 seconds of silence. Multiple regression was performed using known correlates of apnea and ASE to predict PSG levels of respiratory disturbance. Of the commonly known correlates, only self-reported estimate of snoring and apnea severity explained significant variance to the respiratory disturbance index (RDI; R2 = 0.24, p < 0.0001). ASE was entered into the equation as the last step, significantly improving explained variance (R2delta = 0.54, p < 0.0001). The final equation R2 was 78% (p < 0.0001). An alternative analysis compared ASE findings to polysomnographic findings in each matched 30-second interval (60,231 observations) in an analysis of receiver's operating characteristics. This analysis resulted in d' = 2.67, indicating acceptable accuracy for screening.

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Year:  1997        PMID: 9493925     DOI: 10.1093/sleep/20.12.1151

Source DB:  PubMed          Journal:  Sleep        ISSN: 0161-8105            Impact factor:   5.849


  7 in total

1.  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

2.  Acoustic analysis of snoring sounds recorded with a smartphone according to obstruction site in OSAS patients.

Authors:  Soo Kweon Koo; Soon Bok Kwon; Yang Jae Kim; J I Seung Moon; Young Jun Kim; Sung Hoon Jung
Journal:  Eur Arch Otorhinolaryngol       Date:  2016-10-05       Impact factor: 2.503

3.  Validation of the Sonomat: a contactless monitoring system used for the diagnosis of sleep disordered breathing.

Authors:  Mark B Norman; Sally Middleton; Odette Erskine; Peter G Middleton; John R Wheatley; Colin E Sullivan
Journal:  Sleep       Date:  2014-09-01       Impact factor: 5.849

Review 4.  Acoustic Analysis of Snoring in the Diagnosis of Obstructive Sleep Apnea Syndrome: A Call for More Rigorous Studies.

Authors:  Hui Jin; Li-Ang Lee; Lijuan Song; Yanmei Li; Jianxin Peng; Nanshan Zhong; Hsueh-Yu Li; Xiaowen Zhang
Journal:  J Clin Sleep Med       Date:  2015-07-15       Impact factor: 4.062

5.  Detection of compressed tracheal sound patterns with large amplitude variation during sleep.

Authors:  A Kulkas; E Rauhala; E Huupponen; J Virkkala; M Tenhunen; A Saastamoinen; S-L Himanen
Journal:  Med Biol Eng Comput       Date:  2008-02-21       Impact factor: 2.602

6.  Nocturnal snoring sound analysis in the diagnosis of obstructive sleep apnea in the Chinese Han population.

Authors:  Huajun Xu; Wei Song; Hongliang Yi; Limin Hou; Changheng Zhang; Bin Chen; Yuqin Chen; Shankai Yin
Journal:  Sleep Breath       Date:  2014-09-09       Impact factor: 2.816

7.  Obstructive apnea hypopnea index estimation by analysis of nocturnal snoring signals in adults.

Authors:  Nir Ben-Israel; Ariel Tarasiuk; Yaniv Zigel
Journal:  Sleep       Date:  2012-09-01       Impact factor: 5.849

  7 in total

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