[HTML][HTML] Prediction of obstructive sleep apnea using Fast Fourier Transform of overnight breath recordings

NL Molin, C Molin, RJ Dalpatadu, AK Singh - Machine Learning with …, 2021 - Elsevier
The objective of this study is to address the problem of predicting the risk of obstructive sleep
apnea (OSA) from overnight breath recordings collected by a subject using a smartphone or …

Obstructive sleep apnea prediction during wakefulness

A Montazeri, Z Moussavi - … of the IEEE Engineering in Medicine …, 2011 - ieeexplore.ieee.org
In this paper, a novel technique based on signal processing of breath sounds during
wakefulness for prediction of obstructive sleep apnea (OSA) is proposed. We recorded …

[PDF][PDF] A time-series approach to predict obstructive sleep apnea (OSA) Episodes

G Ozdemir, H Nasifoglu, O Erogul - … of the 2nd world congress on …, 2016 - avestia.com
Sleep apnea is a common respiratory disorder during sleep. It is characterized by pauses in
breathing or shallow breathing during sleep for longer than 10 seconds. Except the fact that …

Automated sleep apnea detection in raw respiratory signals using long short-term memory neural networks

T Van Steenkiste, W Groenendaal… - IEEE journal of …, 2018 - ieeexplore.ieee.org
Sleep apnea is one of the most common sleep disorders and the consequences of
undiagnosed sleep apnea can be very severe, ranging from increased blood pressure to …

Identification of obstructive sleep apnea using artificial neural networks and wavelet packet decomposition of the HRV signal

A Hossen, S Qasim - The Journal of Engineering Research …, 2020 - journals.squ.edu.om
The advancement of telecommunication technologies has provided us with new promising
alternatives for remote diagnosis and possible treatment suggestions for patients of diverse …

Obstructive sleep apnea: a prediction model using supervised machine learning method

Z Keshavarz, R Rezaee, M Nasiri… - The Importance of …, 2020 - ebooks.iospress.nl
Abstract Obstructive Sleep Apnea (OSA) is the most common breathing-related sleep
disorder, leading to increased risk of health problems. In this study, we investigated and …

A comparison of regularized logistic regression and random forest machine learning models for daytime diagnosis of obstructive sleep apnea

F Hajipour, MJ Jozani, Z Moussavi - Medical & Biological Engineering & …, 2020 - Springer
A major challenge in big and high-dimensional data analysis is related to the classification
and prediction of the variables of interest by characterizing the relationships between the …

[PDF][PDF] Sleep apnea detection using adaptive neuro fuzzy inference system

C Avci, G Bilgin - Engineering, 2013 - pdfs.semanticscholar.org
This paper presents an efficient and easy implemented method for detecting minute based
analysis of sleep apnea. The nasal, chest and abdominal based respiratory signals …

Automatic respiratory event scoring in obstructive sleep apnea using a long short-term memory neural network

S Nikkonen, H Korkalainen, A Leino… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
The diagnosis of obstructive sleep apnea is based on daytime symptoms and the frequency
of respiratory events during the night. The respiratory events are scored manually from …

Hybridization of soft-computing algorithms with neural network for prediction obstructive sleep apnea using biomedical sensor measurements

MH Chyad, SK Gharghan, HQ Hamood… - Neural Computing and …, 2022 - Springer
Sleep apnea (SA) is a common respiratory disorder, especially among obese people. It is
caused by either the relaxation of the upper respiratory tract muscles or the failure of the …