AIMC Topic: Exercise

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MoveMentor-examining the effectiveness of a machine learning and app-based digital assistant to increase physical activity in adults: protocol for a randomised controlled trial.

Trials
BACKGROUND: Physical inactivity is prevalent, leading to a high burden of disease and large healthcare costs. Thus, there is a need for affordable, effective and scalable interventions. However, interventions that are affordable and scalable are bese...

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...

[From global strategy to local consultation: A future vision of physical activity in primary care].

Atencion primaria
This article reflects on the key role that primary care must play in promoting physical activity as a central tool for health. Despite decades of international strategies, levels of physical inactivity and sedentary behavior continue to rise. The pri...

Machine Learning-Based Prediction of Clinical Outcomes in Patients With Cancer Receiving Systemic Treatment Using Step Count Data Measured With Smartphones.

JCO clinical cancer informatics
PURPOSE: This study aimed to investigate whether changes in step count, measured using patients' own smartphones, could predict a clinical adverse event in the upcoming week in patients undergoing systemic anticancer treatments using machine learning...

Synthesizing Research in Sport and Exercise: Transitioning to Real-World Data and Data Science.

Journal of applied biomechanics
The American Society of Biomechanics (ASB) Jim Hay Memorial Award recognizes individuals for their original long-term contributions to the field of biomechanics. The recipient's work is highlighted at the Jim Hay Symposium held during the ASB annual ...

The urban physical environment and leisure-time physical activity in early midlife: a FinnTwin12 study.

Health & place
Under the exposome framework, this study examined the relationship between the urban physical environment and leisure-time physical activity during early midlife based on 394 participants (mean age: 37, range 34-40) from the FinnTwin12 cohort, residi...

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 ...