Exercise & Fitness

Ranking of non-coding pathogenic variants and putative essential regions of the human genome.

A gene is considered essential if loss of function results in loss of viability, fitness or in disease. This concept is well established for coding genes; however, non-coding regions are thought less likely to be determinants of critical functions. Here we train a machine learning model using functional, mutational and structural features, including new genome essentiality metrics, 3D genome organ...

Novel Descriptors and Digital Signal Processing- Based Method for Protein Sequence Activity Relationship Study.

The work aiming to unravel the correlation between protein sequence and function in the absence of structural information can be highly rewarding. We present a new way of considering descriptors from the amino acids index database for modeling and predicting the fitness value of a polypeptide chain. This approach includes the following steps: (i) Calculating Q elementary numerical sequences (Ele_S...

Optimized artificial neural network based performance analysis of wheelchair movement for ALS patients.

Individuals with neurodegenerative attacks loose the entire motor neuron movements. These conditions affect the individual actions like walking, speak...

Profiling movement behaviours in pre-school children: A self-organised map approach.

Application of machine learning techniques has the potential to yield unseen insights into movement and permits visualisation of complex behaviours an...

An artificial neural network ensemble approach to generate air pollution maps.

The objective of this research is to propose an artificial neural network (ANN) ensemble in order to estimate the hourly NO concentration at unsampled...

Analysis of nonstandardized stress echocardiography sequences using multiview dimensionality reduction.

Alternative stress echocardiography protocols such as handgrip exercise are potentially more favorable towards large-scale screening scenarios than th...

Statistical and machine learning methodology for abdominal aortic aneurysm prediction from ultrasound screenings.

A method of analysis of a database of patients (n = 10 329) screened for an abdominal aortic aneurysm (AAA) is presented. Self-reported height, weight...

Excitation Emission Matrix Fluorescence Spectroscopy for Combustion Generated Particulate Matter Source Identification.

The inhalation of particulate matter (PM) is a significant health risk associated with reduced life expectancy due to increased cardio-pulmonary disea...

Machine learning of human plasma lipidomes for obesity estimation in a large population cohort.

Obesity is associated with changes in the plasma lipids. Although simple lipid quantification is routinely used, plasma lipids are rarely investigated...

Estimation of cerebral blood flow velocity during breath-hold challenge using artificial neural networks.

UNLABELLED: The effect of untreated Obstructive Sleep Apnoea (OSA) on cerebral haemodynamics and CA impairment is an active field of research interest...

Adaptive Neural Sliding-Mode Controller for Alternative Control Strategies in Lower Limb Rehabilitation.

Research on control strategies for rehabilitation robots has gradually shifted from providing therapies with fixed, relatively stiff assistance to com...

Physiological responses and perceived exertion during robot-assisted treadmill walking in non-ambulatory stroke survivors.

PURPOSE: To examine physiological responses and perceived exertion during robot-assisted treadmill walking in non-ambulatory stroke survivors; compare...

Effect of storage on the quality of processed palm oil collected from local milling points within Ile-Ife, Osun State, Nigeria.

The influence of storage practices on physicochemical and microbial changes in crude palm oil (CPO) from milling points in Ile-Ife, Nigeria were inves...

Robotic Exoskeleton for Wrist and Fingers Joint in Post-Stroke Neuro-Rehabilitation for Low-Resource Settings.

Robots have the potential to help provide exercise therapy in a repeatable and reproducible manner for stroke survivors. To facilitate rehabilitation ...

Machine learning and blood pressure.

Machine learning (ML) is a type of artificial intelligence (AI) based on pattern recognition. There are different forms of supervised and unsupervised...

Automated Liver Fat Quantification at Nonenhanced Abdominal CT for Population-based Steatosis Assessment.

Background Nonalcoholic fatty liver disease and its consequences are a growing public health concern requiring cross-sectional imaging for noninvasive...

Nutritional, biochemical and microbiological composition of Mart. sap in Burkina Faso.

The palmyra palm Mart. grow wild and gives natural stands in several localities of central-eastern and eastern regions of Burkina Faso. This work aim...

The effect of using Gait Exercise Assist Robot (GEAR) on gait pattern in stroke patients: a cross-sectional pilot study.

: The Gait Exercise Assist Robot (GEAR) has been developed to support gait training for stroke patients. The GEAR can assist paretic lower limb swing ...

Machine Learning to Understand the Immune-Inflammatory Pathways in Fibromyalgia.

Fibromyalgia (FM) is a chronic syndrome characterized by widespread musculoskeletal pain, and physical and emotional symptoms. Although its pathophysi...

Applying machine learning to predict future adherence to physical activity programs.

BACKGROUND: Identifying individuals who are unlikely to adhere to a physical exercise regime has potential to improve physical activity interventions....