Automatic diagnosis of sleep apnea from biomedical signals using artificial intelligence techniques: Methods, challenges, and future works
P Moridian, A Shoeibi, M Khodatars… - … : Data Mining and …, 2022 - Wiley Online Library
Apnea is a sleep disorder that stops or reduces airflow for a short time during sleep. Sleep
apnea may last for a few seconds and happen for many while sleeping. This reduction in …
apnea may last for a few seconds and happen for many while sleeping. This reduction in …
Sensor-driven achieving of smart living: A review
P Leelaarporn, P Wachiraphan, T Kaewlee… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
This comprehensive review mainly analyzes and summarizes the recently published works
on IEEExplore in sensor-driven smart living contexts. We have gathered over 150 research …
on IEEExplore in sensor-driven smart living contexts. We have gathered over 150 research …
Automatic seizure detection using orthogonal matching pursuit, discrete wavelet transform, and entropy based features of EEG signals
Background and objective Epilepsy is a prevalent disorder that affects the central nervous
system, causing seizures. In the current study, a novel algorithm is developed using …
system, causing seizures. In the current study, a novel algorithm is developed using …
Automatic sleep stage classification using temporal convolutional neural network and new data augmentation technique from raw single-channel EEG
Background and objective: This paper presents a new framework for automatic classification
of sleep stages using a deep learning algorithm from single-channel EEG signals. Each …
of sleep stages using a deep learning algorithm from single-channel EEG signals. Each …
Deep multi-scale fusion neural network for multi-class arrhythmia detection
Automated electrocardiogram (ECG) analysis for arrhythmia detection plays a critical role in
early prevention and diagnosis of cardiovascular diseases. Extracting powerful features from …
early prevention and diagnosis of cardiovascular diseases. Extracting powerful features from …
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 …
OSACN-Net: automated classification of sleep apnea using deep learning model and smoothed Gabor spectrograms of ECG signal
Obstructive sleep apnea (OSA) is a severe sleep-associated respiratory disorder, caused
due to periodic disruption of breath during sleep. It may cause a number of serious …
due to periodic disruption of breath during sleep. It may cause a number of serious …
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 …
A novel hybrid machine learning classification for the detection of bruxism patients using physiological signals
Featured Application 1. The hybrid machine learning (HML) classifier can easily classify the
subjects (healthy and bruxism), sleep stages (w and REM), and both with high accuracy. 2 …
subjects (healthy and bruxism), sleep stages (w and REM), and both with high accuracy. 2 …
Automatic detection of obstructive sleep apnea events using a deep CNN‐LSTM model
J Zhang, Z Tang, J Gao, L Lin, Z Liu… - Computational …, 2021 - Wiley Online Library
Obstructive sleep apnea (OSA) is a common sleep‐related respiratory disorder. Around the
world, more and more people are suffering from OSA. Because of the limitation of monitor …
world, more and more people are suffering from OSA. Because of the limitation of monitor …