ArticleSleep & breathing = Schlaf & Atmung2015
Evaluation of acoustic characteristics of snoring sounds obtained during drug-induced sleep endoscopy.
Article in Sleep & breathing = Schlaf & Atmung, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 17 citations in OpenAlex.
- Noncontact identification of sleep-disturbed breathing from smartphone-recorded sounds validated by polysomnography.Sleep & breathing = Schlaf & Atmung · 2019Trial
- Diagnosis of Obstructive Sleep Apnea Using Feature Selection, Classification Methods, and Data Grouping Based Age, Sex, and Race.Diagnostics (Basel, Switzerland) · 2023Article
- Objective Relationship Between Sleep Apnea and Frequency of Snoring Assessed by Machine Learning.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2019Article
- Review
- Snoring Sounds Predict Obstruction Sites and Surgical Response in Patients with Obstructive Sleep Apnea Hypopnea Syndrome.Scientific reports · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionSnoring sounds are discussed to contain acoustic information about their geneses. Nocturnal snoring can easily be recorded acoustically but it is difficult to visually verify its genesis. Contrary, snoring patterns induced by drug-induced sleep endoscopy (DISE) can be visually differentiated. The aim of the study was to classify patterns of obstructions and vibration during DISE and to evaluate acoustic characteristics between these different patterns of snoring.
methodsDISE was performed in 41 male patients with sleep-disordered breathing. The recorded video sequences (n = 108) were classified visually at a mute mode in different patterns of snoring (velar, velar obstructive, tonsillar, post-apnoeic). The sound tracks of these subgroups were analysed and compared with regard to the parameters sound pressure level, loudness, sharpness, roughness, fluctuations strength and centre frequency.
resultsObstructive snoring patterns revealed a higher loudness than non-obstructive patterns (>25 sone). Velar snoring showed more roughness (>150 cAsper) than tonsillar and post-apnoeic snoring and revealed the lowest centre frequency (<3000 Hz) of all patterns. Tonsillar snoring presented the highest sharpness (>1.6 acum) whereas post-apnoeic snoring revealed the largest fluctuation strength (>50 cVacil).
conclusionDifferent snoring patterns induced by DISE can be classified visually, and an approach to differentiate them acoustically by means of psychoacoustic analyses is demonstrated. On the basis of these results, nocturnal snoring might also be differentiated by psychoacoustic algorithms which could be implemented in acoustic polygraphic screening devices in the future.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.