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Sleep Apnea Syndromes

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ECG Signal Modeling Using Volatility Properties: Its Application in Sleep Apnea Syndrome.

Journal of healthcare engineering
This study presents and evaluates the mathematical model to estimate the mean and variance of single-lead ECG signals in sleep apnea syndrome. Our objective is to use the volatility property of the ECG signal for modeling. ECG signal is a stochastic ...

[Sleep apnea automatic detection method based on convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Sleep apnea (SA) detection method based on traditional machine learning needs a lot of efforts in feature engineering and classifier design. We constructed a one-dimensional convolutional neural network (CNN) model, which consists in four convolution...

Ensemble of Deep Learning Models for Sleep Apnea Detection: An Experimental Study.

Sensors (Basel, Switzerland)
Sleep Apnea is a breathing disorder occurring during sleep. Older people suffer most from this disease. In-time diagnosis of apnea is needed which can be observed by the application of a proper health monitoring system. In this work, we focus on Obst...

SomnNET: An SpO2 Based Deep Learning Network for Sleep Apnea Detection in Smartwatches.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The abnormal pause or rate reduction in breathing is known as the sleep-apnea hypopnea syndrome and affects the quality of sleep of an individual. A novel method for the detection of sleep apnea events (pause in breathing) from peripheral oxygen satu...

Deep-Learning Model Based on Convolutional Neural Networks to Classify Apnea-Hypopnea Events from the Oximetry Signal.

Advances in experimental medicine and biology
Automated analysis of the blood oxygen saturation (SpO) signal from nocturnal oximetry has shown usefulness to simplify the diagnosis of obstructive sleep apnea (OSA), including the detection of respiratory events. However, the few preceding studies ...

Deep Learning Forecasts the Occurrence of Sleep Apnea from Single-Lead ECG.

Cardiovascular engineering and technology
OBJECTIVES: Sleep apnea is the most common sleep disorder that leads to serious health complications if not treated early. Forecasting apnea occurrence ahead in time provides the opportunity to take appropriate actions to control and manage it.

Deep-Learning based Sleep Apnea Detection using SpO2 and Pulse Rate.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This work presents automated apnea event de-tection using blood oxygen saturation (SpO2) and pulse rate (PR), conveniently recorded with a pulse oximeter. A large, diverse cohort of patients (n=8068, age≄40 years) from the sleep heart health study da...

Accurate contactless sleep apnea detection framework with signal processing and machine learning methods.

Methods (San Diego, Calif.)
The detection of sleep apnea is critical for assessing sleep quality. It is also a proven biometric in diagnosing cardiovascular and other diseases. Recent studies have shown that radar-based non-contact vital sign monitoring system can effectively d...

A systematic review of deep learning methods for modeling electrocardiograms during sleep.

Physiological measurement
Sleep is one of the most important human physiological activities, and plays an essential role in human health. Polysomnography (PSG) is the gold standard for measuring sleep quality and disorders, but it is time-consuming, labor-intensive, and prone...

Sleep Apnea Prediction Using Deep Learning.

IEEE journal of biomedical and health informatics
Obstructive sleep apnea (OSA) is a sleep disorder that causes partial or complete cessation of breathing during an individual's sleep. Various methods have been proposed to automatically detect OSA events, but little work has focused on predicting su...