AIMC Topic: Exercise

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The potential role of artificial intelligence to promote the participation and inclusion in physical exercise and sports for people with disabilities: A narrative review.

Journal of bodywork and movement therapies
The lack of physical activity presents a significant public health concern, particularly for individuals with disabilities who face heightened risks due to sedentary lifestyles. Despite progress, personal and environmental obstacles persist, hinderin...

Improving the mapping of leisure-time physical activity inequities: the use of artificial intelligence to advance estimates of small-areas in Brazil.

Public health
OBJECTIVE: We estimated the prevalence of leisure-time physical activity (LTPA) in small areas of the city of Belo Horizonte and analyzed inequities across areas and between two time periods, 2009-2013 and 2014-2018.

Machine Learning and Urinary Incontinence in Prostate Cancer: A Generalized Additive Model of Physical Activity and Recovery Patterns.

Studies in health technology and informatics
The ASCAPE project aims to improve the health-related quality of life of prostate cancer patients using artificial intelligence-driven solutions. This study tries to unravel the complex relationships between patient data variables and urinary inconti...

Processing UK Biobank High Resolution Accelerometry Data for Unsupervised Identification of Activity Profiles and Their Differences in Clinically Relevant Outcome Parameters - The ATLAS Index Revisited.

Studies in health technology and informatics
Accelerometer data obtained with wearable devices over extended periods of time provides objective, valuable information on activity behavior. Building on previous work to derive easy-to-interpret activity parameters - the Activity Types from Long-te...

Designing and Testing a Physical Activity App with a Chatgpt-Based Chatbot.

Studies in health technology and informatics
BACKGROUND AND OBJECTIVE: ChatGPT shows potential as a tool for creating content for health promotion. For example, personalised physical activity (PA) intervention messages can be generated efficiently using ChatGPT. We aimed to develop and test a c...

Long Short-Term Memory Network for Accelerometer-Based Hypertension Classification.

Studies in health technology and informatics
This study investigates the application of a Long Short-Term Memory (LSTM) architecture for classifying hypertension using accelerometer data, specifically focusing on physical activity and sleep from the publicly available NHANES 2011-2012 dataset. ...

Effects of chronic exposure to biomass pollutants on cardiorespiratory responses and the occurrence of exercise-induced bronchoconstriction in healthy men.

Physiological reports
Exposure to charcoal biomass (CB) pollutants affects the cardiorespiratory system. We assessed cardiopulmonary responses (CPR) to exercise in charcoal producers (CPs) compared to farmers and evaluated the prevalence of exercise-induced bronchoconstri...

Exploring the Impact of PA and Sedentary Behavior on Gout Risk in Hyperuricemia: Insights From Machine Learning and SHAP Analysis.

International journal of rheumatic diseases
BACKGROUND: Individuals with hyperuricemia (HUA) are widely recognized as being at increased risk for gout. This study aimed to investigate how physical activity (PA) duration and sedentary duration impact gout risk in individuals with HUA and to dev...

The benefits of physical literacy for human flourishing: A machine learning-based exploration of adolescents.

Applied psychology. Health and well-being
Physical literacy is a multidimensional concept considered fundamental for lifelong participation in physical activity. Although theories on the relationship between physical literacy and human flourishing have been proposed, no comprehensive study o...

Predicting physical functioning status in older adults: insights from wrist accelerometer sensors and derived digital biomarkers of physical activity.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Conventional physical activity (PA) metrics derived from wearable sensors may not capture the cumulative, transitions from sedentary to active, and multidimensional patterns of PA, limiting the ability to predict physical function impairme...