Environmental benefits of sleep apnoea detection in the home environment

R Barika, H Elphick, N Lei, H Razaghi, O Faust - Processes, 2022 - mdpi.com
Sleep Apnoea (SA) is a common chronic illness that affects nearly 1 billion people around
the world, and the number of patients is rising. SA causes a wide range of psychological and …

Robust method for screening sleep apnea with single-lead ecg using deep residual network: evaluation with open database and patch-type wearable device data

M Yeo, H Byun, J Lee, J Byun, HY Rhee… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
This paper proposes a robust method to screen patients with sleep apnea syndrome (SAS)
using a single-lead electrocardiogram (ECG). This method consists of minute-by-minute …

Analysis of smartphone triaxial accelerometry for monitoring sleep-disordered breathing and sleep position at home

I Ferrer-Lluis, Y Castillo-Escario, JM Montserrat… - IEEE …, 2020 - ieeexplore.ieee.org
Obstructive sleep apnea (OSA) is a sleep disorder in which repetitive upper airway
obstructive events occur during sleep. These events can induce hypoxia, which is a risk …

Entropy analysis of acoustic signals recorded with a smartphone for detecting apneas and hypopneas: A comparison with a commercial system for home sleep apnea …

Y Castillo-Escario, I Ferrer-Lluis, JM Montserrat… - IEEE …, 2019 - ieeexplore.ieee.org
Obstructive sleep apnea (OSA) is a prevalent disease, but most patients remain
undiagnosed and untreated. Here we propose analyzing smartphone audio signals for …

Sleeppos app: an automated smartphone application for angle based high resolution sleep position monitoring and treatment

I Ferrer-Lluis, Y Castillo-Escario, JM Montserrat, R Jané - Sensors, 2021 - mdpi.com
Poor sleep quality or disturbed sleep is associated with multiple health conditions. Sleep
position affects the severity and occurrence of these complications, and positional therapy is …

Enhanced monitoring of sleep position in sleep apnea patients: Smartphone triaxial accelerometry compared with video-validated position from polysomnography

I Ferrer-Lluis, Y Castillo-Escario, JM Montserrat, R Jané - Sensors, 2021 - mdpi.com
Poor sleep quality is a risk factor for multiple mental, cardiovascular, and cerebrovascular
diseases. Certain sleep positions or excessive position changes can be related to some …

SleepWatcher: Detecting sleep apnea/hypopnea syndrome from wearable devices using deep learning

H Kim, H Lee, M Kim, YD Chung - Biomedical Signal Processing and …, 2025 - Elsevier
Due to the lack of polysomnography facilities and the cost of testing, it is crucial to detect
sleep apnea/hypopnea syndrome (SAHS) using measurable biomedical signals from a …

Validation of a new, minimally-invasive, software smartphone device to predict sleep apnea and its severity: transversal study

J Frija, J Millet, E Béquignon, A Covali… - arXiv preprint arXiv …, 2024 - arxiv.org
Obstructive sleep apnea (OSA) is frequent and responsible for cardiovascular complications
and excessive daytime sleepiness. It is underdiagnosed due to the difficulty to access the …

Rééducation myofonctionnelle orofaciale et syndrome d'apnées obstructives du sommeil: l'apport de la santé connectée

P Amat, C O'Connor-Reina… - Revue d'Orthopédie Dento …, 2021 - odf.edpsciences.org
La rééducation myofonctionnelle orofaciale (RMOF) a été montrée efficace dans le
traitement multidisciplinaire des syndromes d'apnées obstructives du sommeil (SAOS) de …

A clinical evaluation of a low-cost strain gauge respiration belt and machine learning to detect sleep apnea

S Kristiansen, K Nikolaidis, T Plagemann… - arXiv preprint arXiv …, 2021 - arxiv.org
Sleep apnea is a serious and severely under-diagnosed sleep-related respiration disorder
characterized by repeated disrupted breathing events during sleep. It is diagnosed via …