A survey on ECG analysis
The electrocardiogram (ECG) signal basically corresponds to the electrical activity of the
heart. In the literature, the ECG signal has been analyzed and utilized for various purposes …
heart. In the literature, the ECG signal has been analyzed and utilized for various purposes …
Wearable devices for remote monitoring of heart rate and heart rate variability—what we know and what is coming
Heart rate at rest and exercise may predict cardiovascular risk. Heart rate variability is a
measure of variation in time between each heartbeat, representing the balance between the …
measure of variation in time between each heartbeat, representing the balance between the …
Federated learning of predictive models from federated electronic health records
TS Brisimi, R Chen, T Mela, A Olshevsky… - International journal of …, 2018 - Elsevier
Background In an era of “big data,” computationally efficient and privacy-aware solutions for
large-scale machine learning problems become crucial, especially in the healthcare …
large-scale machine learning problems become crucial, especially in the healthcare …
Deep convolutional neural networks and learning ECG features for screening paroxysmal atrial fibrillation patients
In this paper, a novel computationally intelligent-based electrocardiogram (ECG) signal
classification methodology using a deep learning (DL) machine is developed. The focus is …
classification methodology using a deep learning (DL) machine is developed. The focus is …
A method to detect sleep apnea based on deep neural network and hidden Markov model using single-lead ECG signal
K Li, W Pan, Y Li, Q Jiang, G Liu - Neurocomputing, 2018 - Elsevier
Obstructive sleep apnea (OSA) is the most common sleep-related breathing disorder that
potentially threatened people's cardiovascular system. As an alternative to …
potentially threatened people's cardiovascular system. As an alternative to …
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 …
A novel algorithm for the automatic detection of sleep apnea from single-lead ECG
C Varon, A Caicedo, D Testelmans… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Goal: This paper presents a methodology for the automatic detection of sleep apnea from
single-lead ECG. Methods: It uses two novel features derived from the ECG, and two well …
single-lead ECG. Methods: It uses two novel features derived from the ECG, and two well …
Sleep apnea detection from a single-lead ECG signal with automatic feature-extraction through a modified LeNet-5 convolutional neural network
T Wang, C Lu, G Shen, F Hong - PeerJ, 2019 - peerj.com
Sleep apnea (SA) is the most common respiratory sleep disorder, leading to some serious
neurological and cardiovascular diseases if left untreated. The diagnosis of SA is …
neurological and cardiovascular diseases if left untreated. The diagnosis of SA is …
A sleep apnea detection method based on unsupervised feature learning and single-lead electrocardiogram
K Feng, H Qin, S Wu, W Pan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Sleep apnea (SA) is a harmful respiratory disorder that has caused widespread concern
around the world. Considering that electrocardiogram (ECG)-based SA diagnostic methods …
around the world. Considering that electrocardiogram (ECG)-based SA diagnostic methods …
A review of obstructive sleep apnea detection approaches
Sleep disorders are a common health condition that can affect numerous aspects of life.
Obstructive sleep apnea is one of the most common disorders and is characterized by a …
Obstructive sleep apnea is one of the most common disorders and is characterized by a …