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Exercise Test

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Cardiorespiratory and metabolic demand of the 6-minute pegboard and ring test in healthy young adults.

Journal of bodywork and movement therapies
OBJECTIVE: To determine the cardiorespiratory and metabolic demand of the Six-Minute Pegboard and Ring Test (6PBRT) in healthy young adults and its association with maximal arm cycle ergometer test (arm CET).

Effectiveness of individualized training based on force-velocity profiling on physical function in older men.

Scandinavian journal of medicine & science in sports
The study aimed to investigate the effectiveness of an individualized power training program based on force-velocity (FV) profiling on physical function, muscle morphology, and neuromuscular adaptations in older men. Forty-nine healthy men (68 ± 5 ye...

A Stress Test of Artificial Intelligence: Can Deep Learning Models Trained From Formal Echocardiography Accurately Interpret Point-of-Care Ultrasound?

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: To test if a deep learning (DL) model trained on echocardiography images could accurately segment the left ventricle (LV) and predict ejection fraction on apical 4-chamber images acquired by point-of-care ultrasound (POCUS).

A proposed computer vision model for running gait assessment.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Running gait assessment is critical in performance optimization and injury prevention. Traditional approaches to running gait assessment are inhibited by unnatural running environments (e.g., indoor lab), varied assessor (i.e., subjective experience)...

Fully automated condyle segmentation using 3D convolutional neural networks.

Scientific reports
The aim of this study was to develop an auto-segmentation algorithm for mandibular condyle using the 3D U-Net and perform a stress test to determine the optimal dataset size for achieving clinically acceptable accuracy. 234 cone-beam computed tomogra...

A novel performance scoring quantification framework for stress test set-ups.

PloS one
Stress tests, e.g., the cardiac stress test, are standard clinical screening tools aimed to unmask clinical pathology. As such stress tests indirectly measure physiological reserves. The term reserve has been developed to account for the dis-junction...

Machine Learning Models for the Automatic Detection of Exercise Thresholds in Cardiopulmonary Exercising Tests: From Regression to Generation to Explanation.

Sensors (Basel, Switzerland)
The cardiopulmonary exercise test (CPET) constitutes a gold standard for the assessment of an individual's cardiovascular fitness. A trend is emerging for the development of new machine-learning techniques applied to the automatic process of CPET dat...

Surrogate Modelling for Oxygen Uptake Prediction Using LSTM Neural Network.

Sensors (Basel, Switzerland)
Oxygen uptake (V˙O2) is an important metric in any exercise test including walking and running. It can be measured using portable spirometers or metabolic analyzers. Those devices are, however, not suitable for constant use by consumers due to their ...

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...