[PDF][PDF] Ambient assisted living technologies to support older adults' health and wellness: a systematic mapping review.

MA Choukou, A Polyvyana, Y Sakamoto… - European Review for …, 2021 - europeanreview.org
While the proportion of the Older Adults (OAs) population is growing, this shift raises a
challenging question:“How can we support OAs to lead independent and healthy lifestyle?” …

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 …

Breathing and snoring sound characteristics during sleep in adults

A Levartovsky, E Dafna, Y Zigel… - Journal of Clinical Sleep …, 2016 - jcsm.aasm.org
Study Objectives: Sound level meter is the gold standard approach for snoring evaluation.
Using this approach, it was established that snoring intensity (in dB) is higher for men and is …

AHI estimation of OSAHS patients based on snoring classification and fusion model

Y Song, X Sun, L Ding, J Peng, L Song… - American Journal of …, 2023 - Elsevier
Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a chronic and common sleep-
breathing disease that could negatively influence lives of patients and cause serious …

[HTML][HTML] Assessment of obstructive sleep apnea severity using audio-based snoring features

J Xie, P Fonseca, J van Dijk, S Overeem… - … Signal Processing and …, 2023 - Elsevier
Abstract Background and Objective Snoring is a prima symptom of obstructive sleep apnea
(OSA). Here, we add audio-based snoring features to improve the non-obtrusive …

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 …

Detection of sleep breathing sound based on artificial neural network analysis

T Emoto, UR Abeyratne, K Kawano, T Okada… - … Signal Processing and …, 2018 - Elsevier
Obstructive sleep apnea-hypopnea syndrome (OSAHS) is known to cause daytime
drowsiness and an association with diseases such as Type II diabetes, cardiovascular …

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 …

Noncontact identification of sleep-disturbed breathing from smartphone-recorded sounds validated by polysomnography

S Narayan, P Shivdare, T Niranjan, K Williams… - Sleep and …, 2019 - Springer
Purpose Diagnosis of obstructive sleep apnea by the gold-standard of polysomnography
(PSG), or by home sleep testing (HST), requires numerous physical connections to the …

Breath-by-breath detection of apneic events for OSA severity estimation using non-contact audio recordings

T Rosenwein, E Dafna, A Tarasiuk… - 2015 37th annual …, 2015 - ieeexplore.ieee.org
Obstructive sleep apnea (OSA) is a prevalent sleep disorder, characterized by recurrent
episodes of upper airway obstructions during sleep. We hypothesize that breath-by-breath …