On the generalization of sleep apnea detection methods based on heart rate variability and machine learning
Obstructive sleep apnea (OSA) is a respiratory disorder highly correlated with severe
cardiovascular diseases that has unleashed the interest of hundreds of experts aiming to …
cardiovascular diseases that has unleashed the interest of hundreds of experts aiming to …
Sleep apnea detection from ECG using variational mode decomposition
Sleep apnea is a pervasive breathing problem during night sleep, and its repetitive
occurrence causes various health problems. Polysomnography is commonly used for apnea …
occurrence causes various health problems. Polysomnography is commonly used for apnea …
Sleep apnea detection from ECG signal using deep CNN-based structures
In this paper, transfer learning is used for the adaptation of pre-trained deep convolutional
neural networks (DCNNs) to find the best appropriate method for the classification of …
neural networks (DCNNs) to find the best appropriate method for the classification of …
[HTML][HTML] ECG and SpO2 signal-based real-time sleep apnea detection using feed-forward artificial neural network
Sleep apnea (SA) is a common sleep disorder characterized by respiratory disturbance
during sleep. Polysomnography (PSG) is the gold standard for apnea diagnosis, but it is time …
during sleep. Polysomnography (PSG) is the gold standard for apnea diagnosis, but it is time …
Speed and Accuracy Trade-off ANN/SVM Based Sleep Apnea Detection with FPGA Implementation
During sleep, some people experience breathing difficulties, leading to a condition known
as sleep apnoea, which can result in suffocation. This study focuses on detecting sleep …
as sleep apnoea, which can result in suffocation. This study focuses on detecting sleep …
[HTML][HTML] Improving the understanding of sleep apnea characterization using Recurrence Quantification Analysis by defining overall acceptable values for the …
S Martín-González, JL Navarro-Mesa, G Juliá-Serdá… - PLoS …, 2018 - journals.plos.org
Our contribution focuses on the characterization of sleep apnea from a cardiac rate point of
view, using Recurrence Quantification Analysis (RQA), based on a Heart Rate Variability …
view, using Recurrence Quantification Analysis (RQA), based on a Heart Rate Variability …
[HTML][HTML] Sleep Apnea Detection Using Wavelet Scattering Transformation and Random Forest Classifier
AI Sharaf - Entropy, 2023 - mdpi.com
Obstructive Sleep Apnea (OSA) is a common sleep-breathing disorder that highly reduces
the quality of human life. The most powerful method for the detection and classification of …
the quality of human life. The most powerful method for the detection and classification of …
Usefulness of recurrence plots from airflow recordings to aid in paediatric sleep apnoea diagnosis
V Barroso-García, GC Gutiérrez-Tobal… - Computer Methods and …, 2020 - Elsevier
Background and objective In-laboratory overnight polysomnography (PSG) is the gold
standard method to diagnose the Sleep Apnoea-Hypopnoea Syndrome (SAHS). PSG is a …
standard method to diagnose the Sleep Apnoea-Hypopnoea Syndrome (SAHS). PSG is a …
Real-time implementation of a multidomain feature fusion model using inherently available large sensor data
This paper presents the real-time implementation of a feature fusion based learning using
multidomain discriminant correlation analysis (MDCA) for accurate diagnosis of nonlinear …
multidomain discriminant correlation analysis (MDCA) for accurate diagnosis of nonlinear …
A deep learning model developed for sleep apnea detection: A multi-center study
Objective. Manual detection of obstructive sleep apnea (OSA) is a challenging task for many
reasons such as time-consuming and subjective. This study aimed to develop a deep …
reasons such as time-consuming and subjective. This study aimed to develop a deep …