Sports Medicine

Bone strain index as a predictor of further vertebral fracture in osteoporotic women: An artificial intelligence-based analysis.

BACKGROUND: Osteoporosis is an asymptomatic disease of high prevalence and incidence, leading to bone fractures burdened by high mortality and disability, mainly when several subsequent fractures occur. A fragility fracture predictive model, Artificial Intelligence-based, to identify dual X-ray absorptiometry (DXA) variables able to characterise those patients who are prone to further fractures ca...

Effect of assist-as-needed robotic gait training on the gait pattern post stroke: a randomized controlled trial.

BACKGROUND: Regaining gait capacity is an important rehabilitation goal post stroke. Compared to clinically available robotic gait trainers, robots with an assist-as-needed approach and multiple degrees of freedom (AAN) are expected to support motor learning, and might improve the post-stroke gait pattern. However, their benefits compared to conventional gait training have not yet been shown in a ...

What is the impact of robotic rehabilitation on balance and gait outcomes in people with multiple sclerosis? A systematic review of randomized control trials.

INTRODUCTION: In recent years, robot-assisted gait training (RAGT) has been proposed as therapy for balance and gait dysfunctions in people with multi...

Decision Tree Algorithm Identifies Stroke Patients Likely Discharge Home After Rehabilitation Using Functional and Environmental Predictors.

BACKGROUND AND PURPOSE: The importance of environmental factors for stroke patients to achieve home discharge was not scientifically proven. There are...

Effects of Robotic Therapy Associated With Noninvasive Brain Stimulation on Upper-Limb Rehabilitation After Stroke: Systematic Review and Meta-analysis of Randomized Clinical Trials.

BACKGROUND: Robot-assisted therapy and noninvasive brain stimulation (NIBS) are promising strategies for stroke rehabilitation.

Validation of a Machine Learning Brain Electrical Activity-Based Index to Aid in Diagnosing Concussion Among Athletes.

IMPORTANCE: An objective, reliable indicator of the presence and severity of concussive brain injury and of the readiness for the return to activity h...

Head motion classification using thread-based sensor and machine learning algorithm.

Human machine interfaces that can track head motion will result in advances in physical rehabilitation, improved augmented reality/virtual reality sys...

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...

A Novel Point-in-Polygon-Based sEMG Classifier for Hand Exoskeleton Systems.

In the early 2000s, data from the latest World Health Organization estimates paint a picture where one-seventh of the world population needs at least ...

Systematic review of guidelines to identify recommendations for upper limb robotic rehabilitation after stroke.

INTRODUCTION: Upper limb motor impairment is one of the most frequent stroke consequences. Robot therapy may represent a valid option for upper limb s...

Brain-computer interface robotics for hand rehabilitation after stroke: a systematic review.

BACKGROUND: Hand rehabilitation is core to helping stroke survivors regain activities of daily living. Recent studies have suggested that the use of e...

Robot enhanced stroke therapy optimizes rehabilitation (RESTORE): a pilot study.

BACKGROUND: Robotic rehabilitation after stroke provides the potential to increase and carefully control dosage of therapy. Only a small number of stu...

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 ...

Added value of deep learning-based liver parenchymal CT volumetry for predicting major arterial injury after blunt hepatic trauma: a decision tree analysis.

PURPOSE: In patients presenting with blunt hepatic injury (BHI), the utility of CT for triage to hepatic angiography remains uncertain since simple bi...

Mechanics and Morphological Compensation Strategy for Trimmed Soft Whisker Sensor.

Recent studies have been inspired by natural whiskers for a proposal of tactile sensing system to augment the sensory ability of autonomous robots. In...

Prediction and mechanistic analysis of drug-induced liver injury (DILI) based on chemical structure.

BACKGROUND: Drug-induced liver injury (DILI) is a major safety concern characterized by a complex and diverse pathogenesis. In order to identify DILI ...

Development and Internal Validation of Supervised Machine Learning Algorithms for Predicting Clinically Significant Functional Improvement in a Mixed Population of Primary Hip Arthroscopy.

PURPOSE: To (1) develop and validate a machine learning algorithm to predict clinically significant functional improvements after hip arthroscopy for ...

Resting-state magnetoencephalography source magnitude imaging with deep-learning neural network for classification of symptomatic combat-related mild traumatic brain injury.

Combat-related mild traumatic brain injury (cmTBI) is a leading cause of sustained physical, cognitive, emotional, and behavioral disabilities in Vete...

Forest and Trees: Exploring Bacterial Virulence with Genome-wide Association Studies and Machine Learning.

The advent of inexpensive and rapid sequencing technologies has allowed bacterial whole-genome sequences to be generated at an unprecedented pace. Thi...

Autoperforation of two-dimensional materials to generate colloidal state machines capable of locomotion.

A central ambition of the robotics field has been to increasingly miniaturize such systems, with perhaps the ultimate achievement being the synthetic ...