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 …
Objective sleep assessments for healthy people in environmental research: A literature review
X Xu, Z Lian - Indoor Air, 2022 - Wiley Online Library
To date, although many studies had focused on the impact of environmental factors on
sleep, how to choose the proper assessment method for objective sleep quality was often …
sleep, how to choose the proper assessment method for objective sleep quality was often …
Ensemble-learning regression to estimate sleep apnea severity using at-home oximetry in adults
Overnight pulse oximetry has shown usefulness to simplify obstructive sleep apnea (OSA)
diagnosis when combined with machine-learning approaches. However, the development …
diagnosis when combined with machine-learning approaches. However, the development …
[HTML][HTML] An LSTM network for apnea and hypopnea episodes detection in respiratory signals
J Drzazga, B Cyganek - Sensors, 2021 - mdpi.com
One of the most common sleep disorders is sleep apnea. It manifests itself by episodes of
shallow breathing or pauses in breathing during the night. Diagnosis of this disease involves …
shallow breathing or pauses in breathing during the night. Diagnosis of this disease involves …
[HTML][HTML] Prediction of the sleep apnea severity using 2D-convolutional neural networks and respiratory effort signals
The high prevalence of sleep apnea and the limitations of polysomnography have prompted
the investigation of strategies aimed at automated diagnosis using a restricted number of …
the investigation of strategies aimed at automated diagnosis using a restricted number of …
A Systematic Review on Machine Learning/Deep Learning Model-based Detection of Sleep Apnea Using Bio-Signals
Backgrounds Sleep Apnea (SA) is a sleep-related breathing disorder diagnosed in clinical
laboratories. The gold standard is Polysomnography (PSG), a multi-parameter evaluation of …
laboratories. The gold standard is Polysomnography (PSG), a multi-parameter evaluation of …
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 …
Fine-grained respiratory event detection for SAHS screening
Detecting sleep apnea–hypopnea syndrome (SAHS) through polysomnography (PSG) is
crucial for computer-assisted diagnostics. Although recent advancements in machine …
crucial for computer-assisted diagnostics. Although recent advancements in machine …
A periodic split attractor reconstruction method facilitates cardiovascular signal diagnoses and obstructive sleep apnea syndrome monitoring
Electrocardiogram (ECG) is a powerful tool to detect cardiovascular diseases (CVDs) and
health conditions. We proposed a new method for evaluating ECG for efficient medical …
health conditions. We proposed a new method for evaluating ECG for efficient medical …
A deep learning algorithm model to automatically score and grade obstructive sleep apnea in adult polysomnography
MJ Park, JH Choi, SY Kim, TK Ha - Digital Health, 2024 - journals.sagepub.com
Objective Polysomnography (PSG) is unique in diagnosing sleep disorders, notably
obstructive sleep apnea (OSA). Despite its advantages, manual PSG data grading is time …
obstructive sleep apnea (OSA). Despite its advantages, manual PSG data grading is time …