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Respiration

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Detection of Talking in Respiratory Signals: A Feasibility Study Using Machine Learning and Wearable Textile-Based Sensors.

Sensors (Basel, Switzerland)
Social isolation and loneliness are major health concerns in young and older people. Traditional approaches to monitor the level of social interaction rely on self-reports. The goal of this study was to investigate if wearable textile-based sensors c...

Acute pain intensity monitoring with the classification of multiple physiological parameters.

Journal of clinical monitoring and computing
Current acute pain intensity assessment tools are mainly based on self-reporting by patients, which is impractical for non-communicative, sedated or critically ill patients. In previous studies, various physiological signals have been observed qualit...

Reducing Navigators in Free-Breathing Abdominal MRI via Temporal Interpolation Using Convolutional Neural Networks.

IEEE transactions on medical imaging
Navigated 2-D multi-slice dynamic magnetic resonance imaging (MRI) acquisitions are essential for MR guided therapies. This technique yields time-resolved volumetric images during free-breathing, which are ideal for visualizing and quantifying breath...

Automated Detection of Obstructive Sleep Apnea Events from a Single-Lead Electrocardiogram Using a Convolutional Neural Network.

Journal of medical systems
In this study, we propose a method for the automated detection of obstructive sleep apnea (OSA) from a single-lead electrocardiogram (ECG) using a convolutional neural network (CNN). A CNN model was designed with six optimized convolution layers incl...

Functional-guided radiotherapy using knowledge-based planning.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: There are two significant challenges when implementing functional-guided radiotherapy using 4DCT-ventilation imaging: (1) lack of knowledge of realistic patient specific dosimetric goals for functional lung and (2) ensuring co...

Using Machine Learning and a Combination of Respiratory Flow, Laryngeal Motion, and Swallowing Sounds to Classify Safe and Unsafe Swallowing.

IEEE transactions on bio-medical engineering
OBJECTIVE: The aim of this research was to develop a swallowing assessment method to help prevent aspiration pneumonia. The method uses simple sensors to monitor swallowing function during an individual's daily life.

An alternative method to measure the diffusing capacity of the lung for carbon monoxide in infants.

Pediatric pulmonology
BACKGROUND: Lung diffusion assessed by the uptake of carbon monoxide (DL ) and alveolar volume (V ) by inert gas dilution are readily assessed in cooperative older subjects; however, obtaining these measurements in infants has been much more difficul...

Aerosol delivery during spontaneous breathing with different types of nebulizers- in vitro/ex vivo models evaluation.

Pulmonary pharmacology & therapeutics
BACKGROUND: Nebulizers for spontaneous breathing have been evaluated through different study designs. There are limitations in simulated bench models related to patient and nebulizer factors. The aim of this study was to determine the correlation of ...

Biosignals learning and synthesis using deep neural networks.

Biomedical engineering online
BACKGROUND: Modeling physiological signals is a complex task both for understanding and synthesize biomedical signals. We propose a deep neural network model that learns and synthesizes biosignals, validated by the morphological equivalence of the or...

Neural Network Classifier for Automatic Detection of Invasive Versus Noninvasive Airway Management Technique Based on Respiratory Monitoring Parameters in a Pediatric Anesthesia.

Journal of medical systems
Children undergoing general anesthesia require airway monitoring by an anesthesia provider. The airway may be supported with noninvasive devices such as face mask or invasive devices such as a laryngeal mask airway or an endotracheal tube. The physio...