A review of signals used in sleep analysis

A Roebuck, V Monasterio, E Gederi… - Physiological …, 2013 - iopscience.iop.org
This article presents a review of signals used for measuring physiology and activity during
sleep and techniques for extracting information from these signals. We examine both clinical …

The acoustics of snoring

D Pevernagie, RM Aarts, M De Meyer - Sleep medicine reviews, 2010 - Elsevier
Snoring is a prevalent disorder affecting 20–40% of the general population. The mechanism
of snoring is vibration of anatomical structures in the pharyngeal airway. Flutter of the soft …

A review of current sleep screening applications for smartphones

J Behar, A Roebuck, JS Domingos… - Physiological …, 2013 - iopscience.iop.org
Sleep disorders are a common problem and contribute to a wide range of healthcare issues.
The societal and financial costs of sleep disorders are enormous. Sleep-related disorders …

Detection of sleep disordered breathing severity using acoustic biomarker and machine learning techniques

T Kim, JW Kim, K Lee - Biomedical engineering online, 2018 - Springer
Purpose Breathing sounds during sleep are altered and characterized by various acoustic
specificities in patients with sleep disordered breathing (SDB). This study aimed to identify …

Automatic snoring detection using a hybrid 1D–2D convolutional neural network

R Li, W Li, K Yue, R Zhang, Y Li - Scientific Reports, 2023 - nature.com
Snoring, as a prevalent symptom, seriously interferes with life quality of patients with sleep
disordered breathing only (simple snorers), patients with obstructive sleep apnea (OSA) and …

Automatic detection of whole night snoring events using non-contact microphone

E Dafna, A Tarasiuk, Y Zigel - PloS one, 2013 - journals.plos.org
Objective Although awareness of sleep disorders is increasing, limited information is
available on whole night detection of snoring. Our study aimed to develop and validate a …

An efficient method for snore/nonsnore classification of sleep sounds

M Cavusoglu, M Kamasak, O Erogul… - Physiological …, 2007 - iopscience.iop.org
A new method to detect snoring episodes in sleep sound recordings is proposed. Sleep
sound segments (ie,'sound episodes' or simply'episodes') are classified as snores and …

Automated sleep apnea detection in snoring signal using long short-term memory neural networks

S Cheng, C Wang, K Yue, R Li, F Shen, W Shuai… - … Signal Processing and …, 2022 - Elsevier
Obstructive sleep apnea hypopnea syndrome (OSAHS) is a high incidence disease with
serious hazard and potential danger. The polysomnography (PSG) has become the gold …

Automatic and unsupervised snore sound extraction from respiratory sound signals

A Azarbarzin, ZMK Moussavi - IEEE Transactions on …, 2010 - ieeexplore.ieee.org
In this paper, an automatic and unsupervised snore detection algorithm is proposed. The
respiratory sound signals of 30 patients with different levels of airway obstruction were …

Beyond respiration: Contactless sleep sound-activity recognition using RF signals

C Liu, J Xiong, L Cai, L Feng, X Chen… - Proceedings of the ACM …, 2019 - dl.acm.org
Sleep sound-activities including snore, cough and somniloquy are closely related to sleep
quality, sleep disorder and even illnesses. To obtain the information of these activities …