Effects of Body Position on Snoring in Apneic and Nonapneic Snorers

Nakano, Hiroshi; Ikeda, Togo; Hayashi, Makito; Ohshima, Etsuko; Onizuka, Akihiro

doi:10.1093/sleep/26.2.169

Cited by 86 publications

(60 citation statements)

References 15 publications

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“…8,13,36,37,39 However, our findings ( Figure 5B) do not support earlier studies claiming that snoring intensity is higher in SWS. 36,39 In our subjects AHI ranged from 0.3 to 80 (events/h) and mean individual breathing intensity ranged from 20 to 65 (dB); however, no correlation was found between mean (or upper quarter or top 1%) breathing or snoring intensity and AHI. Our finding is in contrast to earlier reports that found that snoring intensity positively correlated with AHI.…”

Section: Discussioncontrasting

confidence: 99%

“…It is generally accepted that snoring and AHI are very dependent on the body position. 39 Further studies are needed to explore the effect of body position on breathing and snoring sound characteristics. We used a noncontact microphone to record breathing and snoring sounds because this approach enables more natural sleep that is not affected by equipment.…”

Section: Discussionmentioning

confidence: 99%

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Breathing and Snoring Sound Characteristics during Sleep in Adults

Levartovsky

Dafna

Zigel

et al. 2016

Journal of Clinical Sleep Medicine

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Study Objectives: Sound level meter is the gold standard approach for snoring evaluation. Using this approach, it was established that snoring intensity (in dB) is higher for men and is associated with increased apnea-hypopnea index (AHI). In this study, we performed a systematic analysis of breathing and snoring sound characteristics using an algorithm designed to detect and analyze breathing and snoring sounds. The effect of sex, sleep stages, and AHI on snoring characteristics was explored. Methods: We consecutively recruited 121 subjects referred for diagnosis of obstructive sleep apnea. A whole night audio signal was recorded using noncontact ambient microphone during polysomnography. A large number (> 290,000) of breathing and snoring (> 50 dB) events were analyzed. Breathing sound events were detected using a signal-processing algorithm that discriminates between breathing and nonbreathing (noise events) sounds. Results: Snoring index (events/h, SI) was 23% higher for men (p = 0.04), and in both sexes SI gradually declined by 50% across sleep time (p < 0.01) independent of AHI. SI was higher in slow wave sleep (p < 0.03) compared to S2 and rapid eye movement sleep; men have higher SI in all sleep stages than women (p < 0.05). Snoring intensity was similar in both genders in all sleep stages and independent of AHI. For both sexes, no correlation was found between AHI and snoring intensity (r = 0.1, p = 0.291).Conclusions: This audio analysis approach enables systematic detection and analysis of breathing and snoring sounds from a full night recording. Snoring intensity is similar in both sexes and was not affected by AHI.

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Section: Discussioncontrasting

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Breathing and Snoring Sound Characteristics during Sleep in Adults

Levartovsky

Dafna

Zigel

et al. 2016

Journal of Clinical Sleep Medicine

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“…In addition, alarms were infrequent and of short duration during active treatment. Of particular note is that snoring frequency did not change with active treatment, a finding consistent with another report, 38 and difficult to reconcile on the basis of increased wake time. Finally, if AHI on active treatment exclusively represents nonsupine events without changes in wake time, the addition of 19% supine time (ST) to a non-supine AHI (AHI NS ) of ~14 events/h with a 5.3-fold higher supine versus non-supine AHI ratio (AHI Ratio ) would be expected to increase total AHI to ~25 events/h (Expected AHI Total = AHI NS × AHI Ratio × ST + AHI NS × (1-ST) = 14 × 5.3 × 0.19 + 14 × 0.81 = 25.4).…”

Section: Methodological Considerationssupporting

confidence: 77%

Accurate Position Monitoring and Improved Supine-Dependent Obstructive Sleep Apnea with a New Position Recording and Supine Avoidance Device

Bignold

Mercer

Antic³

et al. 2011

Journal of Clinical Sleep Medicine

127

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Study Objectives: Approximately 30% of obstructive sleep apnea (OSA) patients have supine-predominant OSA, and simply avoiding supine sleep should normalise respiratory disturbance event rates. However, traditional supineavoidance therapies are inherently uncomfortable, and treatment adherence is poor and diffi cult to monitor objectively. This study evaluated the effi cacy of a novel, potentially more acceptable position monitor and supine-avoidance device for managing supine-predominant OSA and snoring. Design and Setting: In-laboratory evaluation of position recording accuracy versus video recordings (validation study), and randomized controlled crossover trial of active versus inactive supine-avoidance therapy in the home setting (effi cacy study). Patients: 17 patients undergoing in-laboratory sleep studies (validation) and 15 patients with supine-predominant OSA (effi cacy). Interventions: Effi cacy study: 1 week of inactive and 1 week of active treatment in randomized order, separated by 1 week. Measurements and Results: Agreement between 30-sec epoch-based posture classifi cations from device versus video records was high (median κ 0.95, interquartile range: 0.88-1.00), and there was good supine time agreement (bias 0.3%, 95%CI: −4.0% to 4.6%). In the effi cacy study, apnea-hypopnea index (AHI) and snoring frequency were measured in-home using a nasal pressure and microphone based system during inactive and active treatment weeks. The position monitoring and supine alarm device markedly inhibited supine time (mean ± SEM 19.3% ± 4.3% to 0.4% ± 0.3%, p < 0.001) and reduced AHI (25.0 ± 1.7 to 13.7 ± 1.1 events/h, p = 0.030) but not snoring frequency.

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“…It was shown that the body position during sleep changes both duration and intensity of snoring sounds [27]. However, we did not find a consistent and significant relationship between the sleeping position and the change in the linearity of snoring sound generating process.…”

Section: Resultscontrasting

confidence: 90%

“…The LOOCV is a common technique when the number of observations (subjects in this case) is relatively small; it helps to prevent over-fitting. In the LOOCV, one observation is used as testing set and the rest [27] is used as training set. This procedure is repeated for all observations [28] and the average performance is measured.…”

Section: Classificationmentioning

confidence: 99%

Snoring sounds’ statistical characteristics depend on anthropometric parameters

Azarbarzin¹,

Moussavi²

2012

JBiSE

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Snoring is common in people with obstructive sleep apnea (OSA). Although not every snorer has OSA or vice-versa, many studies attempt to use snoring sounds for classification of people into two groups of OSA and simple snorers. This paper discusses the relationship between snorers' anthropometric parameters and statistical characteristics of snoring sound (SS) and also reports on classification accuracies of methods using SS features for screening OSA from simple snorers when anthropometric parameters are either matched or unmatched. Tracheal respiratory sounds were collected from 60 snorers simultaneously with full-night Polysomnography (PSG). Energy, formant frequency, Skewness and Kurtosis were calculated from the SS segments. We also defined and calculated two features: Median Bifrequency (MBF), and projected MBF (PMBF). The statistical relationship between the extracted features and anthropometric parameters such as height, Body Mass Index (BMI), age, gender, and Apnea-Hypopnea Index (AHI) were investigated. The results showed that the SS features were not only sensitive to AHI but also to height, BMI and gender. Next, we performed two experiments to classify patients with Obstructive Sleep Apnea (OSA) and simple snorers: Experiment A: a small group of participants (22 OSA and 6 simple snorers) with matched height, BMI, and gender were selected and classified using Naïve Bayes classifier, and Experiment B: the same number of participants with unmatched height, BMI, and gender were chosen for classification. A sensitivity of 93.2% (87.5%) and specificity of 88.4% (86.3%) was achieved for the matched (unmatched) groups.

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Effects of Body Position on Snoring in Apneic and Nonapneic Snorers

Cited by 86 publications

References 15 publications

Breathing and Snoring Sound Characteristics during Sleep in Adults

Breathing and Snoring Sound Characteristics during Sleep in Adults

Accurate Position Monitoring and Improved Supine-Dependent Obstructive Sleep Apnea with a New Position Recording and Supine Avoidance Device

Snoring sounds’ statistical characteristics depend on anthropometric parameters

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