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Exercise

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Leisure time physical activity is associated with improved HDL functionality in high cardiovascular risk individuals: a cohort study.

European journal of preventive cardiology
AIMS: Physical activity has consistently been shown to improve cardiovascular health and high-density lipoprotein-cholesterol levels. However, only small and heterogeneous studies have investigated the effect of exercise on high-density lipoprotein f...

Machine learning to quantify habitual physical activity in children with cerebral palsy.

Developmental medicine and child neurology
AIM: To investigate whether activity-monitors and machine learning models could provide accurate information about physical activity performed by children and adolescents with cerebral palsy (CP) who use mobility aids for ambulation.

Identification of Risk Factors Associated with Obesity and Overweight-A Machine Learning Overview.

Sensors (Basel, Switzerland)
Social determining factors such as the adverse influence of globalization, supermarket growth, fast unplanned urbanization, sedentary lifestyle, economy, and social position slowly develop behavioral risk factors in humans. Behavioral risk factors su...

Improving energy expenditure estimates from wearable devices: A machine learning approach.

Journal of sports sciences
A means of quantifying continuous, free-living energy expenditure (EE) would advance the study of bioenergetics. The aim of this study was to apply a non-linear, machine learning algorithm (random forest) to predict minute level EE for a range of act...

Estimating an individual's oxygen uptake during cycling exercise with a recurrent neural network trained from easy-to-obtain inputs: A pilot study.

PloS one
Measurement of oxygen uptake during exercise ([Formula: see text]) is currently non-accessible to most individuals without expensive and invasive equipment. The goal of this pilot study was to estimate cycling [Formula: see text] from easy-to-obtain ...

Application of Raw Accelerometer Data and Machine-Learning Techniques to Characterize Human Movement Behavior: A Systematic Scoping Review.

Journal of physical activity & health
BACKGROUND: Application of machine learning for classifying human behavior is increasingly common as access to raw accelerometer data improves. The aims of this scoping review are (1) to examine if machine-learning techniques can accurately identify ...

Exercise cardiac power and the risk of heart failure in men: A population-based follow-up study.

Journal of sport and health science
BACKGROUND: Little is known about exercise cardiac power (ECP), defined as the ratio of directly measured maximal oxygen uptake with peak systolic blood pressure during exercise, on heart failure (HF) risk. We examined the association of ECP and the ...

Machine Learning Analysis for Quantitative Discrimination of Dried Blood Droplets.

Scientific reports
One of the most interesting and everyday natural phenomenon is the formation of different patterns after the evaporation of liquid droplets on a solid surface. The analysis of dried patterns from blood droplets has recently gained a lot of attention,...

Exercising with Baxter: preliminary support for assistive social-physical human-robot interaction.

Journal of neuroengineering and rehabilitation
BACKGROUND: The worldwide population of older adults will soon exceed the capacity of assisted living facilities. Accordingly, we aim to understand whether appropriately designed robots could help older adults stay active at home.