A review of automated sleep disorder detection
Automated sleep disorder detection is challenging because physiological symptoms can
vary widely. These variations make it difficult to create effective sleep disorder detection …
vary widely. These variations make it difficult to create effective sleep disorder detection …
Computerized detection of cyclic alternating patterns of sleep: A new paradigm, future scope and challenges
Background and objectives: Sleep quality is associated with wellness, and its assessment
can help diagnose several disorders and diseases. Sleep analysis is commonly performed …
can help diagnose several disorders and diseases. Sleep analysis is commonly performed …
SleepContextNet: A temporal context network for automatic sleep staging based single-channel EEG
C Zhao, J Li, Y Guo - Computer Methods and Programs in Biomedicine, 2022 - Elsevier
Background and objective: Single-channel EEG is the most popular choice of sensing
modality in sleep staging studies, because it widely conforms to the sleep staging …
modality in sleep staging studies, because it widely conforms to the sleep staging …
Automated detection of obstructive sleep apnea in more than 8000 subjects using frequency optimized orthogonal wavelet filter bank with respiratory and oximetry …
Obstructive sleep apnea (OSA) is a common respiratory disorder marked by interruption of
the respiratory tract and difficulty in breathing. The risk of serious health damage can be …
the respiratory tract and difficulty in breathing. The risk of serious health damage can be …
CAPSCNet: A novel scattering network for automated identification of phasic cyclic alternating patterns of human sleep using multivariate EEG signals
Abstract The Cyclic Alternating Pattern (CAP) can be considered a physiological marker of
sleep instability. The CAP can examine various sleep-related disorders. Certain short events …
sleep instability. The CAP can examine various sleep-related disorders. Certain short events …
Automated characterization of cyclic alternating pattern using wavelet-based features and ensemble learning techniques with eeg signals
Sleep is highly essential for maintaining metabolism of the body and mental balance for
increased productivity and concentration. Often, sleep is analyzed using macrostructure …
increased productivity and concentration. Often, sleep is analyzed using macrostructure …
Sleep stage classification in EEG signals using the clustering approach based probability distribution features coupled with classification algorithms
W Al-Salman, Y Li, AY Oudah, S Almaged - Neuroscience Research, 2023 - Elsevier
Sleep scoring is one of the primary tasks for the classification of sleep stages in
Electroencephalogram (EEG) signals. Manual visual scoring of sleep stages is time …
Electroencephalogram (EEG) signals. Manual visual scoring of sleep stages is time …
Automated classification of cyclic alternating pattern sleep phases in healthy and sleep-disordered subjects using convolutional neural network
Sleep contributes to more than a third of a person's life, making sleep monitoring essential
for overall well-being. Cyclic alternating patterns (CAP) are crucial in monitoring sleep …
for overall well-being. Cyclic alternating patterns (CAP) are crucial in monitoring sleep …
An automated wavelet-based sleep scoring model using EEG, EMG, and EOG signals with more than 8000 subjects
Human life necessitates high-quality sleep. However, humans suffer from a lower quality of
life because of sleep disorders. The identification of sleep stages is necessary to predict the …
life because of sleep disorders. The identification of sleep stages is necessary to predict the …
An expert system for automated classification of phases in cyclic alternating patterns of sleep using optimal wavelet‐based entropy features
Humans spend a significant portion of their time in the state of sleep, and therefore one's'
sleep health'is an important indicator of the overall health of an individual. Non‐invasive …
sleep health'is an important indicator of the overall health of an individual. Non‐invasive …