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Sleep Stages

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Do all sedatives promote biological sleep electroencephalogram patterns? A machine learning framework to identify biological sleep promoting sedatives using electroencephalogram.

PloS one
BACKGROUND: Sedatives are commonly used to promote sleep in intensive care unit patients. However, it is not clear whether sedation-induced states are similar to the biological sleep. We explored if sedative-induced states resemble biological sleep u...

Automatic Sleep Stage Classification Using Nasal Pressure Decoding Based on a Multi-Kernel Convolutional BiLSTM Network.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sleep quality is an essential parameter of a healthy human life, while sleep disorders such as sleep apnea are abundant. In the investigation of sleep and its malfunction, the gold-standard is polysomnography, which utilizes an extensive range of var...

Multi-Modal Sleep Stage Classification With Two-Stream Encoder-Decoder.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sleep staging serves as a fundamental assessment for sleep quality measurement and sleep disorder diagnosis. Although current deep learning approaches have successfully integrated multimodal sleep signals, enhancing the accuracy of automatic sleep st...

SleepFC: Feature Pyramid and Cross-Scale Context Learning for Sleep Staging.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Automated sleep staging is essential to assess sleep quality and treat sleep disorders, so the issue of electroencephalography (EEG)-based sleep staging has gained extensive research interests. However, the following difficulties exist in this issue:...

Efficient Generalized Electroencephalography-Based Drowsiness Detection Approach with Minimal Electrodes.

Sensors (Basel, Switzerland)
Drowsiness is a main factor for various costly defects, even fatal accidents in areas such as construction, transportation, industry and medicine, due to the lack of monitoring vigilance in the mentioned areas. The implementation of a drowsiness dete...

Driver drowsiness is associated with altered facial thermal patterns: Machine learning insights from a thermal imaging approach.

Physiology & behavior
Driver drowsiness is a significant factor in road accidents. Thermal imaging has emerged as an effective tool for detecting drowsiness by enabling the analysis of facial thermal patterns. However, it is not clear which facial areas are most affected ...

Improved sleep stage predictions by deep learning of photoplethysmogram and respiration patterns.

Computers in biology and medicine
Sleep staging is a crucial tool for diagnosing and monitoring sleep disorders, but the standard clinical approach using polysomnography (PSG) in a sleep lab is time-consuming, expensive, uncomfortable, and limited to a single night. Advancements in s...

A novel deep learning model based on transformer and cross modality attention for classification of sleep stages.

Journal of biomedical informatics
The classification of sleep stages is crucial for gaining insights into an individual's sleep patterns and identifying potential health issues. Employing several important physiological channels in different views, each providing a distinct perspecti...

Comparison of automated deep neural network against manual sleep stage scoring in clinical data.

Computers in biology and medicine
OBJECTIVE: To compare the accuracy and generalizability of an automated deep neural network and the Philip Sleepware G3™ Somnolyzer system (Somnolyzer) for sleep stage scoring using American Academy of Sleep Medicine (AASM) guidelines.

CareSleepNet: A Hybrid Deep Learning Network for Automatic Sleep Staging.

IEEE journal of biomedical and health informatics
Sleep staging is essential for sleep assessment and plays an important role in disease diagnosis, which refers to the classification of sleep epochs into different sleep stages. Polysomnography (PSG), consisting of many different physiological signal...