AIMC Topic: Oxygen Consumption

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Estimating intra- and inter-subject oxygen consumption in outdoor human gait using multiple neural network approaches.

PloS one
Oxygen consumption ([Formula: see text]) is an important measure for exercise test, such as walking and running, that can be measured outdoors using portable spirometers or metabolic analyzers. However, these devices are not feasible for regular use ...

Machine learning prediction of pulmonary oxygen uptake from muscle oxygen in cycling.

Journal of sports sciences
The purpose of this study was to test whether a machine learning model can accurately predict VO across different exercise intensities by combining muscle oxygen (MO) with heart rate (HR). Twenty young highly trained athletes performed the following ...

Machine learning predicts peak oxygen uptake and peak power output for customizing cardiopulmonary exercise testing using non-exercise features.

European journal of applied physiology
PURPOSE: Cardiopulmonary exercise testing (CPET) is considered the gold standard for assessing cardiorespiratory fitness. To ensure consistent performance of each test, it is necessary to adapt the power increase of the test protocol to the physical ...

Effect of robot-assisted gait training on improving cardiopulmonary function in stroke patients: a meta-analysis.

Journal of neuroengineering and rehabilitation
OBJECTIVE: Understanding the characteristics related to cardiorespiratory fitness after stroke can provide reference values for patients in clinical rehabilitation exercise. This meta- analysis aimed to investigate the effect of robot-assisted gait t...

Development, validation, and transportability of several machine-learned, non-exercise-based VO prediction models for older adults.

Journal of sport and health science
BACKGROUND: There exist few maximal oxygen uptake (VO) non-exercise-based prediction equations, fewer using machine learning (ML), and none specifically for older adults. Since direct measurement of VO is infeasible in large epidemiologic cohort stud...

Mechanisms of Exercise Intolerance Across the Breast Cancer Continuum: A Pooled Analysis of Individual Patient Data.

Medicine and science in sports and exercise
PURPOSE: The purpose of this study is to evaluate the prevalence of abnormal cardiopulmonary responses to exercise and pathophysiological mechanism(s) underpinning exercise intolerance across the continuum of breast cancer (BC) care from diagnosis to...

Effect of real-time oxygen consumption versus fixed flow-based low flow anesthesia on oxygenation and perfusion: a randomized, single-blind study.

Medical gas research
Although low-flow anesthesia is widely used due to its various advantages, there are concerns about potential and relative hypoxia. Furthermore, oxygen is also a drug with benefits and adverse effects. We aimed to evaluate and compare the effect of r...

Prediction of oxygen uptake kinetics during heavy-intensity cycling exercise by machine learning analysis.

Journal of applied physiology (Bethesda, Md. : 1985)
Nonintrusive estimation of oxygen uptake (V̇o) is possible with wearable sensor technology and artificial intelligence. V̇o kinetics have been accurately predicted during moderate exercise using easy-to-obtain sensor inputs. However, V̇o prediction a...

Energy Expenditure Estimation in Children, Adolescents and Adults by Using a Respiratory Magnetometer Plethysmography System and a Deep Learning Model.

Nutrients
PURPOSE: Energy expenditure is a key parameter in quantifying physical activity. Traditional methods are limited because they are expensive and cumbersome. Additional portable and cheaper devices are developed to estimate energy expenditure to overco...

QQ-NET - using deep learning to solve quantitative susceptibility mapping and quantitative blood oxygen level dependent magnitude (QSM+qBOLD or QQ) based oxygen extraction fraction (OEF) mapping.

Magnetic resonance in medicine
PURPOSE: To improve accuracy and speed of quantitative susceptibility mapping plus quantitative blood oxygen level-dependent magnitude (QSM+qBOLD or QQ) -based oxygen extraction fraction (OEF) mapping using a deep neural network (QQ-NET).