A review of obstructive sleep apnea detection approaches
F Mendonca, SS Mostafa… - IEEE journal of …, 2018 - ieeexplore.ieee.org
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 …
Detection of sleep apnea using Machine learning algorithms based on ECG Signals: A comprehensive systematic review
Sleep apnea (SA) is a common sleep disorder that is not easy to detect. Recent studies have
highlighted ECG analysis as an effective method of diagnosing SA. Because the changes …
highlighted ECG analysis as an effective method of diagnosing SA. Because the changes …
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 decision support system for automated identification of sleep stages from single-channel EEG signals
A decision support system for automated detection of sleep stages can alleviate the burden
of medical professionals of manually annotating a large bulk of data, expedite sleep disorder …
of medical professionals of manually annotating a large bulk of data, expedite sleep disorder …
Automated identification of sleep states from EEG signals by means of ensemble empirical mode decomposition and random under sampling boosting
AR Hassan, MIH Bhuiyan - Computer methods and programs in …, 2017 - Elsevier
Background and objective: Automatic sleep staging is essential for alleviating the burden of
the physicians of analyzing a large volume of data by visual inspection. It is also a …
the physicians of analyzing a large volume of data by visual inspection. It is also a …
Automatic sleep stage classification using time–frequency images of CWT and transfer learning using convolution neural network
P Jadhav, G Rajguru, D Datta… - Biocybernetics and …, 2020 - Elsevier
For automatic sleep stage classification, the existing methods mostly rely on hand-crafted
features selected from polysomnographic records. In this paper, the goal is to develop a …
features selected from polysomnographic records. In this paper, the goal is to develop a …
Epilepsy seizure detection using complete ensemble empirical mode decomposition with adaptive noise
Background: Epileptic seizure detection is traditionally performed by visual observation of
Electroencephalogram (EEG) signals. Owing to its onerous and time-consuming nature …
Electroencephalogram (EEG) signals. Owing to its onerous and time-consuming nature …
Epileptic seizure detection in EEG signals using tunable-Q factor wavelet transform and bootstrap aggregating
Background and objective Epileptic seizure detection is traditionally performed by expert
clinicians based on visual observation of EEG signals. This process is time-consuming …
clinicians based on visual observation of EEG signals. This process is time-consuming …
Detection of apnea events from ECG segments using Fourier decomposition method
Absence of airflow in breathing during sleep for more than 10 s is known as sleep apnea. It
causes low oxygen levels in the blood which may lead to many cardiovascular problems …
causes low oxygen levels in the blood which may lead to many cardiovascular problems …
Automatic identification of epileptic seizures from EEG signals using linear programming boosting
Background and objective Computerized epileptic seizure detection is essential for
expediting epilepsy diagnosis and research and for assisting medical professionals …
expediting epilepsy diagnosis and research and for assisting medical professionals …