AIMC Topic: Respiration

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A MEMS seismometer respiratory monitor for work of breathing assessment and adventitious lung sounds detection via deep learning.

Scientific reports
Physicians evaluate a patient's respiratory health during a physical examination by visual assessment of the work of breathing (WoB) to determine respiratory stability, and by detecting abnormal lung sounds via lung auscultation using a stethoscope t...

Convolutional long short-term memory neural network integrated with classifier in classifying type of asynchrony breathing in mechanically ventilated patients.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Asynchronous breathing (AB) occurs when a mechanically ventilated patient's breathing does not align with the mechanical ventilator (MV). Asynchrony can negatively impact recovery and outcome, and/or hinder MV management. A ...

Interpretable machine learning models for COPD ease of breathing estimation.

Medical & biological engineering & computing
Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide and greatly reduces the quality of life. Utilizing remote monitoring has been shown to improve quality of life and reduce exacerbations, but remains an ongoing area of...

Prediction of real-time cine-MR images during MRI-guided radiotherapy of liver cancer using a GAN-ConvLSTM network.

Medical physics
BACKGROUND: Respiratory motion during radiotherapy (RT) may reduce the therapeutic effect and increase the dose received by organs at risk. This can be addressed by real-time tracking, where respiration motion prediction is currently required to comp...

Machine learning-based estimation of respiratory fluctuations in a healthy adult population using resting state BOLD fMRI and head motion parameters.

Magnetic resonance in medicine
PURPOSE: External physiological monitoring is the primary approach to measure and remove effects of low-frequency respiratory variation from BOLD-fMRI signals. However, the acquisition of clean external respiratory data during fMRI is not always poss...

Deep learning-based approach for acquisition time reduction in ventilation SPECT in patients after lung transplantation.

Radiological physics and technology
We aimed to evaluate the image quality and diagnostic performance of chronic lung allograft dysfunction (CLAD) with lung ventilation single-photon emission computed tomography (SPECT) images acquired briefly using a convolutional neural network (CNN)...

Electrocardiogram and respiration recordings show a reduction in the physical burden on professional caregivers when performing care tasks with a transfer support robot.

Assistive technology : the official journal of RESNA
In this study, we assessed the physical burden on professional caregivers when using a transfer support robot, "Hug," to transfer and move a care recipient. We compared heart rate (HR), heart rate variability (HRV), and the time-series synchronizatio...

Classification of mindfulness experiences from gamma-band effective connectivity: Application of machine-learning algorithms on resting, breathing, and body scan.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Practicing mindfulness is a mental process toward interoceptive awareness, achieving stress reduction and emotion regulation through brain-function alteration. Literature has shown that electroencephalography (EEG)-derived c...

PPG2RespNet: a deep learning model for respirational signal synthesis and monitoring from photoplethysmography (PPG) signal.

Physical and engineering sciences in medicine
Breathing conditions affect a wide range of people, including those with respiratory issues like asthma and sleep apnea. Smartwatches with photoplethysmogram (PPG) sensors can monitor breathing. However, current methods have limitations due to manual...

Deep-learning-assisted thermogalvanic hydrogel fiber sensor for self-powered in-nostril respiratory monitoring.

Journal of colloid and interface science
Direct and consistent monitoring of respiratory patterns is crucial for disease prognostication. Although the wired clinical respiratory monitoring apparatus can operate accurately, the existing defects are evident, such as the indispensability of an...