AIMC Topic: Exercise

Clear Filters Showing 1 to 10 of 334 articles

Knee injury prevention via personalized exercise using EDAS method and Sugeno Weber operator under complex q rung orthopair fuzzy data.

Scientific reports
Knee injuries are common in several people, frequently controlling for significant injuries and health care costs. This article explains the role of personalized exercise prescriptions in preventing knee injuries. For this purpose, we used the multic...

Improved convolutional neural network for precise exercise posture recognition and intelligent health indicator prediction.

Scientific reports
This paper presents a novel framework for accurate exercise posture recognition and health indicator prediction based on improved convolutional neural networks. We propose a multi-scale feature fusion architecture incorporating spatiotemporal attenti...

How does social support influence autonomous physical learning in adolescents? Evidence from a chain mediation and latent profile analysis.

PloS one
PURPOSE: This study examines how social support influences adolescents' autonomous physical learning behavior, exploring the mediating roles of self-efficacy and exercise motivation, and the moderating effects of gender and behavioral typologies. The...

Energy consumption analysis and prediction in exercise training based on accelerometer sensors and deep learning.

Scientific reports
This study aims to enhance the accuracy and efficiency of energy consumption prediction during exercise training and address the limitations of existing methods in terms of data feature extraction, model complexity, and adaptability to practical appl...

Using Large Language Models to Enhance Exercise Recommendations and Physical Activity in Clinical and Healthy Populations: Scoping Review.

JMIR medical informatics
BACKGROUND: Regular exercise recommendations (ERs) and physical activity (PA) are crucial for the prevention and management of chronic diseases. However, creating effective exercise programs demand substantial time and specialized expertise from both...

Deep learning to promote health through sports and physical training.

Frontiers in public health
BACKGROUND: Physical activity plays a crucial role in maintaining health and preventing chronic diseases. However, accurately assessing the impact of sports and physical training on health improvement remains a challenge. Recent advancements in deep ...

Characterising physical activity patterns in community-dwelling older adults using digital phenotyping: a 2-week observational study protocol.

BMJ open
INTRODUCTION: Physical activity (PA) is crucial for older adults' well-being and mitigating health risks. Encouraging active lifestyles requires a deeper understanding of the factors influencing PA, which conventional approaches often overlook by ass...

[Cluster predictors of trajectories of leisure-time physical activity intensity in men and women from ELSA-Brasil].

Cadernos de saude publica
The maintenance of physical activity over time is a challenge for public health. Predictors of different physical activity intensities have not been sufficiently analyzed. This study aimed to identify clusters of trajectories of physical activity int...

Potential Modulatory Roles of Gut Microbiota and Metabolites in the Associations of Macronutrient-to-Physical Activity Ratios With Dyslipidemia.

Journal of the American Heart Association
BACKGROUND: Lifestyle factors toward diet and physical activity (PA) may directly influence the pathophysiology of dyslipidemia. However, the associations of the specific macronutrient-to-PA ratio with dyslipidemia, and the underlying mechanisms rega...

Uncovering key factors in weight loss effectiveness through machine learning.

International journal of obesity (2005)
BACKGROUND/OBJECTIVES: One of the main challenges in weight loss is the dramatic interindividual variability in response to treatment. We aim to systematically identify factors relevant to weight loss effectiveness using machine learning (ML).