Sleep apnea classification using random forest via ECG
AP Razi, Z Einalou, M Manthouri - Sleep and Vigilance, 2021 - Springer
Sleep apnea (SA) is among the most common sleep-related disorders, which is defined as
the interruption of airflow in the airways for at least 10 s. Apnea can lead to different types of …
the interruption of airflow in the airways for at least 10 s. Apnea can lead to different types of …
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 …
[PDF][PDF] Constant Q-transform-based deep learning architecture for detection of obstructive sleep apnea
UR Kandukuri, AJ Prakash, KK Patro… - … Journal of Applied …, 2023 - intapi.sciendo.com
Obstructive sleep apnea (OSA) is a long-term sleep disorder that causes temporary
disruption in breathing while sleeping. Polysomnography (PSG) is the technique for …
disruption in breathing while sleeping. Polysomnography (PSG) is the technique for …
Wearable respiratory rate sensor technology for diagnosis of sleep apnea
Sleep apnea is a disease that occurs during sleep, which affects the daily life of patients due
to the obstruction of the upper respiratory tract and decreases oxygen level in blood and it …
to the obstruction of the upper respiratory tract and decreases oxygen level in blood and it …
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 …
Topological descriptors of gait nonlinear dynamics toward freezing-of-gait episodes recognition in parkinson's disease
Gait complexity analysis and nonlinear dynamics descriptions were widely used in abnormal
state detection in disease studies. Recent development in algebra topology brought novel …
state detection in disease studies. Recent development in algebra topology brought novel …
Applicability of continuous, stationary, and discrete wavelet transforms in engineering signal processing
Wavelet-based signal processing techniques are widely applied in multiple disciplines.
However, few studies consider the applicability of different wavelet transforms in …
However, few studies consider the applicability of different wavelet transforms in …
Complexity-aided time series modeling and forecasting under a decomposition-aggregation framework
M Song, R Wang - Information Sciences, 2024 - Elsevier
Complexity of time series has always been of significant interest to researchers; however, it
is not yet effectively explored in assisting time series prediction modeling. In this study, we …
is not yet effectively explored in assisting time series prediction modeling. In this study, we …
[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 …
[HTML][HTML] Deep Learning Modeling of Cardiac Arrhythmia Classification on Information Feature Fusion Image with Attention Mechanism
M Zhang, H Jin, B Zheng, W Luo - Entropy, 2023 - mdpi.com
The electrocardiogram (ECG) is a crucial tool for assessing cardiac health in humans.
Aiming to enhance the accuracy of ECG signal classification, a novel approach is proposed …
Aiming to enhance the accuracy of ECG signal classification, a novel approach is proposed …