Prevention

On the Impact of Biceps Muscle Fatigue in Human Activity Recognition.

Nowadays, Human Activity Recognition (HAR) systems, which use wearables and smart systems, are a part of our daily life. Despite the abundance of literature in the area, little is known about the impact of muscle fatigue on these systems' performance. In this work, we use the biceps concentration curls exercise as an example of a HAR activity to observe the impact of fatigue impact on such systems...

Oxynet: A collective intelligence that detects ventilatory thresholds in cardiopulmonary exercise tests.

The problem of the automatic determination of the first and second ventilatory thresholds (VT1 and VT2) from cardiopulmonary exercise test (CPET) still leads to controversy. The reliability of the gold standard methodology (i.e. expert visual inspection) feeds into the debate and several authors call for more objective automatic methods to be used in the clinical practice. In this study, we presen...

The Metabolic Cost of Exercising With a Robotic Exoskeleton: A Comparison of Healthy and Neurologically Impaired People.

While neuro-recovery is maximized through active engagement, it has been suggested that the use of robotic exoskeletons in neuro-rehabilitation provid...

Analyzing Description, User Understanding and Expectations of AI in Mobile Health Applications.

Previous research has studied medical professionals' perception of artificial intelligence (AI). However, there has been a limited understanding of ho...

Supported progressive resistance exercise training to counter the adverse side effects of robot-assisted radical prostatectomy: a randomised controlled trial.

PURPOSE: To investigate the effects of a supported home-based progressive resistance exercise training (RET) programme on indices of cardiovascular he...

The art of robotic colonic resection: a review of progress in the past 5 years.

Surgery is developing in the direction of minimal invasiveness, and robotic surgery is becoming increasingly adopted in colonic resection procedures. ...

Ranking of a wide multidomain set of predictor variables of children obesity by machine learning variable importance techniques.

The increased prevalence of childhood obesity is expected to translate in the near future into a concomitant soaring of multiple cardio-metabolic dise...

Smartphone-based human fatigue level detection using machine learning approaches.

Human muscle fatigue is the main result of diminishing muscle capability, leading to reduced performance and increased risk of falls and injury. This ...

Establishing key research questions for the implementation of artificial intelligence in colonoscopy: a modified Delphi method.

BACKGROUND : Artificial intelligence (AI) research in colonoscopy is progressing rapidly but widespread clinical implementation is not yet a reality. ...

Analysing the predictive capacity and dose-response of wellness in load monitoring.

This study aimed to identify the predictive capacity of wellness questionnaires on measures of training load using machine learning methods. The distr...

Classification of intestinal T-cell receptor repertoires using machine learning methods can identify patients with coeliac disease regardless of dietary gluten status.

In coeliac disease (CeD), immune-mediated small intestinal damage is precipitated by gluten, leading to variable symptoms and complications, occasiona...

The Combined Effects of Sports Smart Bracelet and Multi-Component Exercise Program on Exercise Motivation among the Elderly in Macau.

Faced with the serious problem of an aging population, exercise is one of the most effective ways to maintain the health of the elderly. In recent ye...

Caffeine mouth rinse enhances performance, fatigue tolerance and reduces muscle activity during moderate-intensity cycling.

We investigated the effects of caffeine mouth rinse on endurance performance, muscle recruitment (i.e., electromyographic activity of the vastus later...

Use of a convolutional neural network and quantitative ultrasound for diagnosis of fatty liver.

Quantitative ultrasound (QUS) was used to classify rabbits that were induced to have liver disease by placing them on a fatty diet for a defined durat...

An embedded system for the automated generation of labeled plant images to enable machine learning applications in agriculture.

A lack of sufficient training data, both in terms of variety and quantity, is often the bottleneck in the development of machine learning (ML) applica...

Optimising an FFQ Using a Machine Learning Pipeline to teach an Efficient Nutrient Intake Predictive Model.

Food frequency questionnaires (FFQs) are the most commonly selected tools in nutrition monitoring, as they are inexpensive, easily implemented and pro...

Precision medicine in the era of artificial intelligence: implications in chronic disease management.

Aberrant metabolism is the root cause of several serious health issues, creating a huge burden to health and leading to diminished life expectancy. A ...

Data-Driven Robust Control for a Closed-Loop Artificial Pancreas.

We present a fully closed-loop design for an artificial pancreas (AP) that regulates the delivery of insulin for the control of Type I diabetes. Our A...

A Process Evaluation Examining the Performance, Adherence, and Acceptability of a Physical Activity and Diet Artificial Intelligence Virtual Health Assistant.

Artificial intelligence virtual health assistants are a promising emerging technology. This study is a process evaluation of a 12-week pilot physical ...

Comparison of a Deep Learning-Based Pose Estimation System to Marker-Based and Kinect Systems in Exergaming for Balance Training.

Using standard digital cameras in combination with deep learning (DL) for pose estimation is promising for the in-home and independent use of exercise...