AIMC Topic: Exercise Test
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Comparing the Prognostic Value of Stress Myocardial Perfusion Imaging by Conventional and Cadmium-Zinc Telluride Single-Photon Emission Computed Tomography through a Machine Learning Approach.
Computational and mathematical methods in medicine
Oct 16, 2021
We compared the prognostic value of myocardial perfusion imaging (MPI) by conventional- (C-) single-photon emission computed tomography (SPECT) and cadmium-zinc-telluride- (CZT-) SPECT in a cohort of patients with suspected or known coronary artery d...
Cardiorespiratory and metabolic demand of the 6-minute pegboard and ring test in healthy young adults.
Journal of bodywork and movement therapies
Oct 9, 2021
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).
Estimation of Mechanical Power Output Employing Deep Learning on Inertial Measurement Data in Roller Ski Skating.
Sensors (Basel, Switzerland)
Sep 29, 2021
The ability to optimize power generation in sports is imperative, both for understanding and balancing training load correctly, and for optimizing competition performance. In this paper, we aim to estimate mechanical power output by employing a time-...
A Soft Robotic Intervention for Gait Enhancement in Older Adults.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 14, 2021
Falls continue to be a major safety and health concern for older adults. Researchers reported that increased gait variability was associated with increased fall risks. In the present study, we proposed a novel wearable soft robotic intervention and e...
Machine Learning for personalised stress detection: Inter-individual variability of EEG-ECG markers for acute-stress response.
Computer methods and programs in biomedicine
Aug 8, 2021
Stress appears as a response for a broad variety of physiological stimuli. It does vary among individuals in amplitude, phase and frequency. Thus, the necessity for personalised diagnosis is key to prevent stress-related diseases. In order to evaluat...
A Machine Learning Approach to the Interpretation of Cardiopulmonary Exercise Tests: Development and Validation.
Pulmonary medicine
May 31, 2021
OBJECTIVE: At present, there is no consensus on the best strategy for interpreting the cardiopulmonary exercise test's (CPET) results. This study is aimed at assessing the potential of using computer-aided algorithms to evaluate CPET data for identif...
Oxynet: A collective intelligence that detects ventilatory thresholds in cardiopulmonary exercise tests.
European journal of sport science
Jan 31, 2021
The problem of the automatic determination of the first and second ventilatory thresholds (VT1 and VT2) from cardiopulmonary exercise test (CPET) still leads to controversy. The reliability of the gold standard methodology (i.e. expert visual inspect...
Artificial Intelligence-Assisted motion capture for medical applications: a comparative study between markerless and passive marker motion capture.
Computer methods in biomechanics and biomedical engineering
Dec 8, 2020
We aimed to determine whether artificial intelligence (AI)-assisted markerless motion capture software is useful in the clinical medicine and rehabilitation fields. Currently, it is unclear whether the AI-assisted markerless method can be applied to ...
Dyspnea, effort and muscle pain during exercise in lung transplant recipients: an analysis of their association with cardiopulmonary function parameters using machine learning.
Respiratory research
Oct 15, 2020
BACKGROUND: Despite improvement in lung function, most lung transplant (LTx) recipients show an unexpectedly reduced exercise capacity that could be explained by persisting peripheral muscle dysfunction of multifactorial origin. We analyzed the cours...
New Machine Learning Approach for Detection of Injury Risk Factors in Young Team Sport Athletes.
International journal of sports medicine
Sep 13, 2020
The purpose of this article is to present how predictive machine learning methods can be utilized for detecting sport injury risk factors in a data-driven manner. The approach can be used for finding new hypotheses for risk factors and confirming the...
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