AIMC Topic: Physical Fitness

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Advancing training effectiveness prediction in mass sport through longitudinal data: A mathematical model approach based on the Fitness-Fatigue Model.

PloS one
Despite the critical need for scientific training load assessment in mass sports, the Fitness-Fatigue Model (FFM) requires further mathematical optimization and practical output indicators. The aim of this study was to optimize the mathematical relat...

A Smartphone Platform for Remote Motor Fitness Assessment and AI-Generated Personalized Exercise Programs for Older Adults: Randomized Controlled Trial.

Journal of medical Internet research
BACKGROUND: Exercise guidelines for older adults are predominantly "one-size-fits-all," primarily focusing on aerobic activity with limited emphasis on motor components.

Impact of Preseason Training Camps on Fitness, Fatigue, and Performance in Professional Football Players: Mildaltitude Camp Versus Sea-Level Camp.

International journal of sports physiology and performance
PURPOSE: Preseason in football is crucial for optimizing physical fitness, team cohesion, and tactical readiness. This study investigated the effects of 2 distinct preseason training environments-mild altitude with cooler conditions and sea level wit...

Predicting Maximal Military Occupational Task Performance from Physical Fitness Tests Using Machine Learning.

Medicine and science in sports and exercise
PURPOSE: Optimal performance in military tasks is crucial for operational success. These tasks are often simulated in training, assessing personnel performance within a military environment. However, these assessments are time-consuming and a potenti...

Transforming physical fitness and exercise behaviors in adolescent health using a life log sharing model.

Frontiers in public health
INTRODUCTION: This study investigates the potential of a deep learning-based Life Log Sharing Model (LLSM) to enhance adolescent physical fitness and exercise behaviors through personalized public health interventions.

The impact of preschool children's physical fitness evaluation under self organizing maps neural network.

Scientific reports
To improve the scientific accuracy and precision of children's physical fitness evaluations, this study proposes a model that combines self-organizing maps (SOM) neural networks with cluster analysis. Existing evaluation methods often rely on traditi...

Neural network model for prediction of possible sarcopenic obesity using Korean national fitness award data (2010-2023).

Scientific reports
Sarcopenic obesity (SO) is characterized by concomitant sarcopenia and obesity and presents a high risk of disability, morbidity, and mortality among older adults. However, predictions based on sequential neural network SO studies and the relationshi...

Method for Incomplete and Imbalanced Data Based on Multivariate Imputation by Chained Equations and Ensemble Learning.

IEEE journal of biomedical and health informatics
The classification analysis of incomplete and imbalanced data is still a challenging task since these issues could negatively impact the training of classifiers, which were also found in our study on the physical fitness assessments of patients. And ...

Predicting Soccer Players' Fitness Status Through a Machine-Learning Approach.

International journal of sports physiology and performance
PURPOSE: The study had 3 purposes: (1) to develop an index using machine-learning techniques to predict the fitness status of soccer players, (2) to explore the index's validity and its relationship with a submaximal run test (SMFT), and (3) to analy...

Identifying Behavior Change Techniques in an Artificial Intelligence-Based Fitness App: A Content Analysis.

Health education & behavior : the official publication of the Society for Public Health Education
In the field of artificial intelligence-based fitness apps, the effective integration of behavior change techniques (BCTs) is critical for promoting physical activity and improving health outcomes. However, the specific BCTs employed by apps and thei...