AIMC Topic: Exercise
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Interpretable machine learning for identifying overweight and obesity risk factors of older adults in China.
Geriatric nursing (New York, N.Y.)
Jan 4, 2025
OBJECTIVE: To estimate the importance of risk factors on overweight/obesity among older adults by comparing different predictive model.
Estimating cardiovascular mortality in patients with hypertension using machine learning: The role of depression classification based on lifestyle and physical activity.
Journal of psychosomatic research
Dec 29, 2024
PURPOSE: This study aims to harness machine learning techniques, particularly the Random Survival Forest (RSF) model, to assess the impact of depression on cardiovascular disease (CVD) mortality among hypertensive patients. A key objective is to eluc...
Digital phenotyping from heart rate dynamics: Identification of zero-poles models with data-driven evolutionary learning.
Computers in biology and medicine
Dec 27, 2024
Heart rate response to physical activity is widely investigated in clinical and training practice, as it provides information on a person's physical state. For emerging digital phenotyping approaches, there is a need for individualized model estimati...
Breath Analyzer for Real-Time Exercise Fat Burning Prediction: Oral and Alveolar Breath Insights with CNN.
ACS sensors
Dec 23, 2024
The increasing prevalence of obesity and metabolic disorders has created a significant demand for personalized devices that can effectively monitor fat metabolism. In this study, we developed an advanced breath analyzer system designed to provide rea...
Effect of wearable robot Bot Fit's hip joint-centered assist torque and voice coach on walking.
BMC musculoskeletal disorders
Dec 23, 2024
BACKGROUND: The main key to the 4th industrial era is robots, and wearable robots are incorporated into human healthcare. Samsung Electronics' Bot Fit is a hip joint-centered assistive robot that can induce walking posture and energetic walking exerc...
Core reference ontology for individualized exercise prescription.
Scientific data
Dec 18, 2024
"Exercise is medicine" emphasizes personalized prescriptions for better efficacy. Current guidelines need more support for personalized prescriptions, posing scientific challenges. Facing those challenges, we gathered data from established guidelines...
Machine learning derived physical activity in preschool children with developmental coordination disorder.
Developmental medicine and child neurology
Dec 10, 2024
AIM: To compare the device-measured physical activity behaviours of preschool children with typical motor development to those with probable developmental coordination disorder (pDCD) and at risk for developmental coordination disorder (DCDr).
DS-MS-TCN: Otago Exercises Recognition With a Dual-Scale Multi-Stage Temporal Convolutional Network.
IEEE journal of biomedical and health informatics
Dec 5, 2024
The Otago Exercise Program (OEP) represents a crucial rehabilitation initiative tailored for older adults, aimed at enhancing balance and strength. Despite previous efforts utilizing wearable sensors for OEP recognition, existing studies have exhibit...
Can people with epilepsy trust AI chatbots for information on physical exercise?
Epilepsy & behavior : E&B
Dec 4, 2024
PURPOSE: This study aims to evaluate the similarity, readability, and alignment with current scientific knowledge of responses from AI-based chatbots to common questions about epilepsy and physical exercise.
The factors affecting aerobics athletes' performance using artificial intelligence neural networks with sports nutrition assistance.
Scientific reports
Nov 28, 2024
This work aims to comprehensively explore the influencing factors of aerobics athletes' performance by integrating sports nutrition assistance and artificial intelligence neural networks. First, a personalized assessment and analysis of athletes' nut...
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