ReviewHNO2017
[Acoustic information in snoring noises].
Review in HNO, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- A Bag of Wavelet Features for Snore Sound Classification.Annals of biomedical engineering · 2019Trial
- Interpretable Acoustic Features from Wakefulness Tracheal Breathing for OSA Severity Assessment.Journal of clinical medicine · 2026Article
- Deep learning approaches for image-based snoring sound analysis in the diagnosis of obstructive sleep apnea-hypopnea syndrome: A systematic review.World journal of radiology · 2025Article
- Automatic detection of obstructive sleep apnea based on speech or snoring sounds: a narrative review.Journal of thoracic disease · 2024Review
- [VOTE versus ACLTE: comparison of two snoring noise classifications using machine learning methods].HNO · 2019Article
- Prediction of Obstructive Sleep Apnea Based on Respiratory Sounds Recorded Between Sleep Onset and Sleep Offset.Clinical and experimental otorhinolaryngology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMore than one third of all people snore regularly. Snoring is a common accompaniment of obstructive sleep apnea (OSA) and is often disruptive for the bed partner.
objectiveThis work gives an overview of the history of and state of research on acoustic analysis of snoring for classification of OSA severity, detection of obstructive events, measurement of annoyance, and identification of the sound excitation location. MATERIALS AND
methodsBased on these objectives, searches were conducted in the literature databases PubMed and IEEE Xplore. Publications dealing with the respective objectives according to title and abstract were selected from the search results.
resultsA total of 48 publications concerning the above objectives were considered. The limiting factor of many studies is the small number of subjects upon which the analyses are based.
conclusionRecent research findings show promising results, such that acoustic analysis may find a place in the framework of sleep diagnostics, thus supplementing the recognized standard methods.
Indexed as
Identifiers
28108791What 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.