A RR interval based automated apnea detection approach using residual network
Abstract Background and Objective Apnea is one of the most common conditions that
causes sleep-disorder breathing. With growing number of patients worldwide, more and …
causes sleep-disorder breathing. With growing number of patients worldwide, more and …
Accurate detection of sleep apnea with long short-term memory network based on RR interval signals
Sleep apnea is a common condition that is characterized by sleep-disordered breathing.
Worldwide the number of apnea cases has increased and there has been a growing number …
Worldwide the number of apnea cases has increased and there has been a growing number …
Sleep apnea detection from single-lead ECG using features based on ECG-derived respiration (EDR) signals
P Janbakhshi, MB Shamsollahi - Irbm, 2018 - Elsevier
Background and objective One of the important applications of non-invasive respiration
monitoring using ECG signal is the detection of obstructive sleep apnea (OSA). ECG-derived …
monitoring using ECG signal is the detection of obstructive sleep apnea (OSA). ECG-derived …
Greedy based convolutional neural network optimization for detecting apnea
SS Mostafa, D Baptista, AG Ravelo-García… - Computer Methods and …, 2020 - Elsevier
Background and objective Sleep apnea is a common sleep disorder, usually diagnosed
using an expensive, highly specialized, and inconvenient test called polysomnography. A …
using an expensive, highly specialized, and inconvenient test called polysomnography. A …
Detection of sleep apnea using deep neural networks and single-lead ECG signals
Sleep apnea causes frequent cessation of breathing during sleep. Feature extraction
approaches play a key role in the performance of apnea detection algorithms that use single …
approaches play a key role in the performance of apnea detection algorithms that use single …
Multiscale deep neural network for obstructive sleep apnea detection using RR interval from single-lead ECG signal
Q Shen, H Qin, K Wei, G Liu - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The detection of obstructive sleep apnea (OSA) based on single-lead electrocardiogram
(ECG) is better suited to the noninvasive needs and hardware conditions of wearable mobile …
(ECG) is better suited to the noninvasive needs and hardware conditions of wearable mobile …
Robust method for screening sleep apnea with single-lead ecg using deep residual network: evaluation with open database and patch-type wearable device data
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 …
using a single-lead electrocardiogram (ECG). This method consists of minute-by-minute …
Detection of sleep apnea from single-lead ECG: Comparison of deep learning algorithms
M Bahrami, M Forouzanfar - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Apnea is a prevalent sleep disorder which has detrimental impacts on human health and
quality of life. Accurate automatic algorithms for the detection of sleep apnea are needed for …
quality of life. Accurate automatic algorithms for the detection of sleep apnea are needed for …
Deep learning approaches for automatic detection of sleep apnea events from an electrocardiogram
U Erdenebayar, YJ Kim, JU Park, EY Joo… - Computer methods and …, 2019 - Elsevier
Abstract Background and Objective This study demonstrates deep learning approaches with
an aim to find the optimal method to automatically detect sleep apnea (SA) events from an …
an aim to find the optimal method to automatically detect sleep apnea (SA) events from an …
Contribution of different subbands of ECG in sleep apnea detection evaluated using filter bank decomposition and a convolutional neural network
CY Yeh, HY Chang, JY Hu, CC Lin - Sensors, 2022 - mdpi.com
A variety of feature extraction and classification approaches have been proposed using
electrocardiogram (ECG) and ECG-derived signals for improving the performance of …
electrocardiogram (ECG) and ECG-derived signals for improving the performance of …