AIMC Topic: Exercise Test

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Development of deep-learning models for real-time anaerobic threshold and peak VO2 prediction during cardiopulmonary exercise testing.

European journal of preventive cardiology
AIMS: Exercise intolerance is a clinical feature of patients with heart failure (HF). Cardiopulmonary exercise testing (CPET) is the first-line examination for assessing exercise capacity in patients with HF. However, the need for extensive experienc...

Deep Learning for Multiple Sclerosis Differentiation Using Multi-Stride Dynamics in Gait.

IEEE transactions on bio-medical engineering
OBJECTIVE: Multiple sclerosis (MS) is a chronic neurological condition of the central nervous system leading to various physical, mental and psychiatric complexities. Mobility limitations are amongst the most frequent and early markers of MS. We eval...

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)...

Treadmill-Based Locomotor Training With Robotic Pelvic Assist and Visual Feedback: A Feasibility Study.

Journal of neurologic physical therapy : JNPT
BACKGROUND AND PURPOSE: Gait asymmetries are common after stroke, and often persist despite conventional rehabilitation. Robots provide training at a greater practice frequency than conventional approaches. However, prior studies of have found the tr...

PycnoRacer®, a fitness drink including Pycnogenol®, improves recovery and training in the Cooper test.

Panminerva medica
BACKGROUND: This study evaluates the effects of training (on running distance measured with a Cooper test) in 3 weeks in non-professional athletes using PycnoRacer®, a fitness drink (FD) including Pycnogenol® during the training period.

Neural Networks for Prognostication of Patients With Heart Failure.

Circulation. Heart failure
Background Prognostication of heart failure patients from cardiopulmonary exercise test (CPET) currently involves simplification of complex time-series data into summary indices. We hypothesized that prognostication could be improved by considering t...

Influence of the amount of body weight support on lower limb joints' kinematics during treadmill walking at different gait speeds: Reference data on healthy adults to define trajectories for robot assistance.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Several robotic devices have been developed for the rehabilitation of treadmill walking in patients with movement disorders due to injuries or diseases of the central nervous system. These robots induce coordinated multi-joint movements aimed at repr...

Machine Learning Analysis of Left Ventricular Function to Characterize Heart Failure With Preserved Ejection Fraction.

Circulation. Cardiovascular imaging
BACKGROUND: Current diagnosis of heart failure with preserved ejection fraction (HFpEF) is suboptimal. We tested the hypothesis that comprehensive machine learning (ML) of left ventricular function at rest and exercise objectively captures difference...