Exercise & Fitness

Age-specific risk factors for the prediction of obesity using a machine learning approach.

Machine Learning is a powerful tool to discover hidden information and relationships in various data-driven research fields. Obesity is an extremely complex topic, involving biological, physiological, psychological, and environmental factors. One successful approach to the topic is machine learning frameworks, which can reveal complex and essential risk factors of obesity. Over the last two decade...

Systematic Review of Machine Learning applied to the Prediction of Obesity and Overweight.

Obesity and overweight has increased in the last year and has become a pandemic disease, the result of sedentary lifestyles and unhealthy diets rich in sugars, refined starches, fats and calories. Machine learning (ML) has proven to be very useful in the scientific community, especially in the health sector. With the aim of providing useful tools to help nutritionists and dieticians, research focu...

Machine Learning Models for the Automatic Detection of Exercise Thresholds in Cardiopulmonary Exercising Tests: From Regression to Generation to Explanation.

The cardiopulmonary exercise test (CPET) constitutes a gold standard for the assessment of an individual's cardiovascular fitness. A trend is emerging...

Leg Muscle Activity and Joint Motion during Balance Exercise Using a Newly Developed Weight-Shifting-Based Robot Control System.

A novel and fun exercise robot (LOCOBOT) was developed to improve balance ability. This system can control a spherical robot on a floor by changing th...

Using machine learning to predict the effects and consequences of mutations in proteins.

Machine and deep learning approaches can leverage the increasingly available massive datasets of protein sequences, structures, and mutational effects...

Smartphones dependency risk analysis using machine-learning predictive models.

Recent technological advances have changed how people interact, run businesses, learn, and use their free time. The advantages and facilities provided...

Behaviour recommendations with a deep learning model and genetic algorithm for health debt characterisation.

Human behaviour is a dense longitudinal multi-featured measure that directly impacts the health of individuals in the short and long terms. Therefore,...

Profiling Physical Fitness of Physical Education Majors Using Unsupervised Machine Learning.

The academic curriculum has shown to promote sedentary behavior in college students. This study aimed to profile the physical fitness of physical educ...

Automatic Assessment of Functional Movement Screening Exercises with Deep Learning Architectures.

(1) Background: The success of physiotherapy depends on the regular and correct unsupervised performance of movement exercises. A system that automati...

Use of Robot-Assisted Gait Training in Pediatric Patients with Cerebral Palsy in an Inpatient Setting-A Randomized Controlled Trial.

Robot-assisted gait training (RAGT) provides a task-based support of walking using exoskeletons. Evidence shows moderate, but positive effects in the ...

Teleoperation control of a wheeled mobile robot based on Brain-machine Interface.

This paper presents a novel teleoperation system using Electroencephalogram (EEG) to control the motion of a wheeled mobile robot (WMR). Different fro...

Robotic training for medical students: feasibility of a pilot simulation curriculum.

While robotic procedures are growing rapidly, medical students have a limited role in robotic surgeries. Curricula are needed to enhance engagement. W...

A novel hybrid optimization enabled robust CNN algorithm for an IoT network intrusion detection approach.

Due to the huge number of connected Internet of Things (IoT) devices within a network, denial of service and flooding attacks on networks are on the r...

Optimization for a New XY Positioning Mechanism by Artificial Neural Network-Based Metaheuristic Algorithms.

This paper devotes a new method in modeling and optimizing to handle the optimization of the XY positioning mechanism. The fitness functions and const...

Artificial intelligence model with deep learning in nonalcoholic fatty liver disease diagnosis: genetic based artificial neural networks.

Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease in the world. The NAFLD spectrum includes simple st...

A stochastic numerical approach for a class of singular singularly perturbed system.

In the present study, a neuro-evolutionary scheme is presented for solving a class of singular singularly perturbed boundary value problems (SSP-BVPs)...

Development and validation of a mathematical model to simulate human cardiovascular and respiratory responses to battlefield trauma.

Mathematical models of human cardiovascular and respiratory systems provide a viable alternative to generate synthetic data to train artificial intell...

Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation.

Leading a sedentary lifestyle may cause numerous health problems. Therefore, passive lifestyle changes should be given priority to avoid severe long-t...

Direct Evaluation of Treatment Response in Brain Metastatic Disease with Deep Neuroevolution.

Cancer centers have an urgent and unmet clinical and research need for AI that can guide patient management. A core component of advancing cancer trea...

Cytologic scoring of equine exercise-induced pulmonary hemorrhage: Performance of human experts and a deep learning-based algorithm.

Exercise-induced pulmonary hemorrhage (EIPH) is a relevant respiratory disease in sport horses, which can be diagnosed by examination of bronchoalveol...