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Exercise

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Clinical outcomes of hospitalised individuals with spin-induced exertional rhabdomyolysis.

Annals of the Academy of Medicine, Singapore
INTRODUCTION: Exertional rhabdomyolysis (ER) is caused by myocyte breakdown after strenuous physical activity. In recent years, the incidence of spin-induced ER (SER) has been increasing. We describe the clinical characteristics, management and outco...

Comparing cadence-based and machine learning based estimates for physical activity intensity classification: The UK Biobank.

Journal of science and medicine in sport
OBJECTIVES: Cadence thresholds have been widely used to categorize physical activity intensity in health-related research. We examined the convergent validity of two cadence-based intensity classification approaches against a machine-learning-based i...

Using explainable machine learning and fitbit data to investigate predictors of adolescent obesity.

Scientific reports
Sociodemographic and lifestyle factors (sleep, physical activity, and sedentary behavior) may predict obesity risk in early adolescence; a critical period during the life course. Analyzing data from 2971 participants (M = 11.94, SD = 0.64 years) wear...

Workout Classification Using a Convolutional Neural Network in Ensemble Learning.

Sensors (Basel, Switzerland)
To meet the increased demand for home workouts owing to the COVID-19 pandemic, this study proposes a new approach to real-time exercise posture classification based on the convolutional neural network (CNN) in an ensemble learning system. By utilizin...

A CNN Model for Physical Activity Recognition and Energy Expenditure Estimation from an Eyeglass-Mounted Wearable Sensor.

Sensors (Basel, Switzerland)
Metabolic syndrome poses a significant health challenge worldwide, prompting the need for comprehensive strategies integrating physical activity monitoring and energy expenditure. Wearable sensor devices have been used both for energy intake and ener...

The development of an EU-wide nutrition and physical activity expert knowledge base to support a personalised mobile application across various EU population groups.

Nutrition bulletin
A healthy lifestyle comprising regular physical activity and an adequate diet is imperative for the prevention of non-communicable diseases such as hypertension and some cancers. Advances in information computer technology offer the opportunity to pr...

Real-Time Sensor-Based Human Activity Recognition for eFitness and eHealth Platforms.

Sensors (Basel, Switzerland)
Human Activity Recognition (HAR) plays an important role in the automation of various tasks related to activity tracking in such areas as healthcare and eldercare (telerehabilitation, telemonitoring), security, ergonomics, entertainment (fitness, spo...

Identifying the risk of exercises, recommended by an artificial intelligence for patients with musculoskeletal disorders.

Scientific reports
Musculoskeletal disorders (MSDs) impact people globally, cause occupational illness and reduce productivity. Exercise therapy is the gold standard treatment for MSDs and can be provided by physiotherapists and/or also via mobile apps. Apart from the ...

A Data-Driven Approach to Predicting Recreational Activity Participation Using Machine Learning.

Research quarterly for exercise and sport
With the popularity of recreational activities, the study aimed to develop prediction models for recreational activity participation and explore the key factors affecting participation in recreational activities. A total of 12,712 participants, exc...

Human Factors in AI-Driven Digital Solutions for Increasing Physical Activity: Scoping Review.

JMIR human factors
BACKGROUND: Artificial intelligence (AI) has the potential to enhance physical activity (PA) interventions. However, human factors (HFs) play a pivotal role in the successful integration of AI into mobile health (mHealth) solutions for promoting PA. ...