AIMC Topic: Sedentary Behavior

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Nonlinear Associations of Accelerometer-Based Sedentary Time With Cognitive Functions in the UK Biobank.

The journals of gerontology. Series B, Psychological sciences and social sciences Jun 10, 2025
OBJECTIVES: Device-based sedentary time shows a nonlinear association with incident dementia among older adults. However, associations between sedentary time and cognitive performance have been inconsistent. We examined potential nonlinear associatio...
Cognition Biological Specimen Banks Nonlinear Dynamics Male Middle Aged Neuropsychological Tests Sedentary Behavior UK Biobank United Kingdom Accelerometry Female Aged Humans
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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 Apr 1, 2025
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...
Aged Adult Female Risk Factors Risk Assessment Exercise Time Factors Male Middle Aged Humans Biomarkers Retrospective Studies Machine Learning Sedentary Behavior Gout Nutrition Surveys United States Hyperuricemia Uric Acid
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A Machine Learning Approach for Prediction of Sedentary Behavior Based on Daily Step Counts.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Sedentary behavior is considered as a major public health challenge, linked with many chronic diseases and premature mortality. In this paper, we propose a steps counting -based machine learning approach for the prediction of sedentary behavior. Our ...
Sedentary Behavior Algorithms Logistic Models Neural Networks, Computer Machine Learning Humans
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Free-living Evaluation of Laboratory-based Activity Classifiers in Preschoolers.

Medicine and science in sports and exercise May 1, 2020
UNLABELLED: Machine learning classification models for accelerometer data are potentially more accurate methods to measure physical activity in young children than traditional cut point methods. However, existing algorithms have been trained on labor...
Fitness Trackers Humans Video Recording Sedentary Behavior Reproducibility of Results Games, Recreational Accelerometry Child, Preschool Walking Child Development Exercise Support Vector Machine Running
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A Dual-Accelerometer System for Classifying Physical Activity in Children and Adults.

Medicine and science in sports and exercise Dec 1, 2018
INTRODUCTION: Accurately monitoring 24-h movement behaviors is a vital step for progressing the time-use epidemiology field. Past accelerometer-based measurement protocols are either hindered by lack of wear time compliance, or the inability to accur...
Sedentary Behavior Adult Back Male Thigh Adolescent Humans Machine Learning Accelerometry Middle Aged Female Child Exercise Models, Theoretical
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Towards a Personal Health Record System for the Assesment and Monitoring of Sedentary Behavior in Indoor Locations.

Studies in health technology and informatics Jan 1, 2016
BACKGROUND: Sedentary behavior has been associated to the development of noncommunicable diseases (NCD) such as cardiovascular diseases (CVD), type 2 diabetes, and cancer. Accelerometers and inclinometers have been used to estimate sedentary behavior...
Supervised Machine Learning Posture Wireless Technology Sedentary Behavior Humans Health Records, Personal Accelerometry Algorithms
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