Exercise & Fitness

A Combined Hot and Hypoxic Environment during Maximal Cycling Sprints Reduced Muscle Oxygen Saturation: A Pilot Study.

The present study investigated the effects of a combined hot and hypoxic environment on muscle oxygenation during repeated 15-s maximal cycling sprints. In a single-blind, cross-over study, nine trained sprinters performed three 15-s maximal cycling sprints interspersed with 7-min passive recovery in normoxic (NOR; 23℃, 50%, FiO 20.9%), normobaric hypoxic (HYP; 23℃, FiO 14.5%), and hot normobaric ...

Feature Selection and Validation of a Machine Learning-Based Lower Limb Risk Assessment Tool: A Feasibility Study.

Early and self-identification of locomotive degradation facilitates us with awareness and motivation to prevent further deterioration. We propose the usage of nine squat and four one-leg standing exercise features as input parameters to Machine Learning (ML) classifiers in order to perform lower limb skill assessment. The significance of this approach is that it does not demand manpower and infras...

Predicting the Risk of Hypertension Based on Several Easy-to-Collect Risk Factors: A Machine Learning Method.

Hypertension is a widespread chronic disease. Risk prediction of hypertension is an intervention that contributes to the early prevention and manageme...

Skeletal muscle myostatin gene expression and sarcopenia in overweight and obese middle-aged and older adults.

BACKGROUND: Myostatin (MSTN) is a key negative regulator of muscle mass in humans and animals, having direct and indirect influences on molecular regu...

Renal Functional and Perioperative Outcomes of Retroperitoneal Robot-Assisted Versus Laparoscopic Partial Nephrectomy with Segmental Renal Artery Clamping.

Retroperitoneal approach and segmental renal artery clamping in partial nephrectomy are techniques that facilitate postoperative recovery and renal f...

Deep Integration of Physical Health Education Based on Intelligent Communication Technology.

In recent years, intelligent medical communication technology has developed rapidly, and the advancement of hardware technology has accelerated the de...

Evaluation of Teachers' Educational Technology Ability Based on Fuzzy Clustering Generalized Regression Neural Network.

The improvement of teachers' educational technology ability is one of the main methods to improve the management efficiency of colleges and universiti...

Discrimination of vascular aging using the arterial pulse spectrum and machine-learning analysis.

Aging contributes to the progression of vascular dysfunction and is a major nonreversible risk factor for cardiovascular disease. The aim of this stud...

Deep learning models for benign and malign ocular tumor growth estimation.

Relatively abundant availability of medical imaging data has provided significant support in the development and testing of Neural Network based image...

Model-based data augmentation for user-independent fatigue estimation.

OBJECTIVE: User-independent recognition of exercise-induced fatigue from wearable motion data is challenging, due to inter-participant variability. Th...

Robotic devices for paediatric rehabilitation: a review of design features.

Children with physical disabilities often have limited performance in daily activities, hindering their physical development, social development and m...

Intravenous Iron Replacement Improves Exercise Tolerance in COPD: A Single-Blind Randomized Trial.

INTRODUCTION: Iron deficiency affects exercise capacity because of the critical role iron plays in the optimal functioning of skeletal muscle metaboli...

Upper-Limb Motion Recognition Based on Hybrid Feature Selection: Algorithm Development and Validation.

BACKGROUND: For rehabilitation training systems, it is essential to automatically record and recognize exercises, especially when more than one type o...

Epistatic Net allows the sparse spectral regularization of deep neural networks for inferring fitness functions.

Despite recent advances in high-throughput combinatorial mutagenesis assays, the number of labeled sequences available to predict molecular functions ...

Deep learning multimodal fNIRS and EEG signals for bimanual grip force decoding.

Non-invasive brain-machine interfaces (BMIs) offer an alternative, safe and accessible way to interact with the environment. To enable meaningful and ...

Sociodemographic risk factors of under-five stunting in Bangladesh: Assessing the role of interactions using a machine learning method.

This paper aims to demonstrate the importance of studying interactions among various sociodemographic risk factors of childhood stunting in Bangladesh...

Extremely randomized neural networks for constructing prediction intervals.

The aim of this paper is to propose a novel prediction model based on an ensemble of deep neural networks adapting the extremely randomized trees meth...

Informed training set design enables efficient machine learning-assisted directed protein evolution.

Directed evolution of proteins often involves a greedy optimization in which the mutation in the highest-fitness variant identified in each round of s...

A machine learning approach to predict extreme inactivity in COPD patients using non-activity-related clinical data.

Facilitating the identification of extreme inactivity (EI) has the potential to improve morbidity and mortality in COPD patients. Apart from patients ...

Recommendations for marathon runners: on the application of recommender systems and machine learning to support recreational marathon runners.

Every year millions of people, from all walks of life, spend months training to run a traditional marathon. For some it is about becoming fit enough t...