Real-time prediction of upcoming respiratory events via machine learning using snoring sound signal

B Wang, X Yi, J Gao, Y Li, W Xu, J Wu… - Journal of Clinical Sleep …, 2021 - jcsm.aasm.org
Study Objectives: The aim of the study was to inspect the acoustic properties and sleep
characteristics of a preapneic snoring sound. The feasibility of forecasting upcoming …

[HTML][HTML] Prediction of obstructive sleep apnea based on respiratory sounds recorded between sleep onset and sleep offset

JW Kim, T Kim, J Shin, G Choe, HJ Lim… - Clinical and …, 2019 - synapse.koreamed.org
Objectives To develop a simple algorithm for prescreening of obstructive sleep apnea (OSA)
on the basis of respiratorysounds recorded during polysomnography during all sleep stages …

Evaluating prediction models of sleep apnea from smartphone-recorded sleep breathing sounds

SW Cho, SJ Jung, JH Shin, TB Won… - … –Head & Neck …, 2022 - jamanetwork.com
Importance Breathing sounds during sleep are an important characteristic feature of
obstructive sleep apnea (OSA) and have been regarded as a potential biomarker. Breathing …

Obstructive sleep apnea detection based on sleep sounds via deep learning

B Wang, X Tang, H Ai, Y Li, W Xu… - Nature and Science of …, 2022 - Taylor & Francis
Purpose This study aimed to propose a novel deep-learning method for automatic sleep
apneic event detection and thus to estimate the apnea hypopnea index (AHI) and identify …

Obstructive Sleep Apnea Classification Using Snore Sounds Based on Deep Learning

A Sillaparaya, A Bhatranand… - 2022 Asia-Pacific …, 2022 - ieeexplore.ieee.org
Early screening for the Obstructive Sleep Apnea (OSA), especially the first grade of Apnea-
Hypopnea Index (AHI), can reduce risk and improve the effectiveness of timely treatment …

Tracheal sound analysis using a deep neural network to detect sleep apnea

H Nakano, T Furukawa, T Tanigawa - Journal of Clinical Sleep …, 2019 - jcsm.aasm.org
Study Objectives: Portable devices for home sleep apnea testing are often limited by their
inability to discriminate sleep/wake status, possibly resulting in underestimations. Tracheal …

Correlation analysis of sleep breathing sound and polysomnographic features

JW Kim, SW Cho, K Lee, JY Shin - 2019 - Eur Respiratory Soc
OBJECTIVE: To find relationship between sleep breathing sounds and various
polysomnographic features. METHOD: Patients who underwent PSG with audio recording …

Automated Detection of Sleep Apnea Using Machine Learning: A Novel Approach Using Smartphone and Microphone for Breathing Sound Analysis

O Bhatt - medRxiv, 2024 - medrxiv.org
In this study, we evaluate the accuracy of a novel setup in the detection of apneas and
hypopneas and estimating the apnea-hypopnea index (AHI). The study device setup …

Can machine learning assist locating the excitation of snore sound? A review

K Qian, C Janott, M Schmitt, Z Zhang… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
In the past three decades, snoring (affecting more than 30% adults of the UK population) has
been increasingly studied in the transdisciplinary research community involving medicine …

Automatic snoring signal analysis in sleep studies

R Jané, JA Fiza, J Solà-Soler, S Blanch… - Proceedings of the …, 2003 - ieeexplore.ieee.org
Snoring has been related to vibration of upper airway during sleep. It has been reported in
the literature as a risk factor of different diseases, such as obstructive sleep apnea syndrome …