Sports Medicine

Machine learning algorithms can classify outdoor terrain types during running using accelerometry data.

BACKGROUND: Running is a popular physical activity that benefits health; however, running surface characteristics may influence loading impact and injury risk. Machine learning algorithms could automatically identify running surface from wearable motion sensors to quantify running exposures, and perhaps loading and injury risk for a runner.

Unilateral vs Bilateral Hybrid Approaches for Upper Limb Rehabilitation in Chronic Stroke: A Randomized Controlled Trial.

OBJECTIVE: To investigate the effects of unilateral hybrid therapy (UHT) and bilateral hybrid therapy (BHT) compared with robot-assisted therapy (RT) alone in patients with chronic stroke.

Time-delay estimation based computed torque control with robust adaptive RBF neural network compensator for a rehabilitation exoskeleton.

A new approach to gait rehabilitation task of a 12 DOF lower limb exoskeleton is proposed combining time-delay estimation (TDE) based computed torque ...

New Motion Intention Acquisition Method of Lower Limb Rehabilitation Robot Based on Static Torque Sensors.

The rehabilitation robot is an application of robotic technology for people with limb disabilities. This paper investigates a new applicable and effec...

Development of a biological signal-based evaluator for robot-assisted upper-limb rehabilitation: a pilot study.

Bio-signal based assessment for upper-limb functions is an attractive technology for rehabilitation. In this work, an upper-limb function evaluator is...

Trust in socially assistive robots: Considerations for use in rehabilitation.

Incorporation of social robots into rehabilitation calls for understanding what factors affect user motivation and success of the interaction. Trust b...

Influences of the biofeedback content on robotic post-stroke gait rehabilitation: electromyographic vs joint torque biofeedback.

BACKGROUND: Add-on robot-mediated therapy has proven to be more effective than conventional therapy alone in post-stroke gait rehabilitation. Such rob...

Robot-Assisted Arm Training in Chronic Stroke: Addition of Transition-to-Task Practice.

. Robot-assisted therapy provides high-intensity arm rehabilitation that can significantly reduce stroke-related upper extremity (UE) deficits. Motor ...

Validation of computerized square-drawing based evaluation of motor function in patients with stroke.

Human-administered clinical scales are commonly used for quantifying motor performance and determining the course of therapy in post-stroke individual...

Learning the implicit strain reconstruction in ultrasound elastography using privileged information.

Quasi-static ultrasound elastography is an importance imaging technology to assess the conditions of various diseases through reconstructing the tissu...

Robotic-assisted therapy with bilateral practice improves task and motor performance in the upper extremities of chronic stroke patients: A randomised controlled trial.

BACKGROUND/AIM: Task-specific repetitive training, a usual care in occupational therapy practice, and robotic-aided rehabilitation with bilateral prac...

Acute stroke rehabilitation for gait training with cyborg type robot Hybrid Assistive Limb: A pilot study.

Robot-assisted gait training following acute stroke could allow patients with severe disability to receive a high dosage and intensity of gait trainin...

A review of cable-driven rehabilitation devices.

To conduct a survey on the research and development of cable-driven rehabilitation devices (CDRDs). This review searches in the databases of PubMed,...

Iterative processes: a review of semi-supervised machine learning in rehabilitation science.

To define semi-supervised machine learning (SSML) and explore current and potential applications of this analytic strategy in rehabilitation research...

On-field player workload exposure and knee injury risk monitoring via deep learning.

In sports analytics, an understanding of accurate on-field 3D knee joint moments (KJM) could provide an early warning system for athlete workload expo...

Morphology-based classification of mycobacteria-infected macrophages with convolutional neural network: reveal EsxA-induced morphologic changes indistinguishable by naked eyes.

EsxA is an essential virulence factor for Mycobacterium tuberculosis (Mtb) pathogenesis as well as an important biomarker for Mtb detection. In this s...

Efficacy of Cardiac Rehabilitation with Assistance from Hybrid Assistive Limb in Patients with Chronic Heart Failure: Protocol for a Randomized Controlled Study.

The hybrid assistive limb (HAL) provides motion assistance based on bioelectrical signals detected on the skin surface when muscle forces are generate...

A neural network model predicts community-level signaling states in a diverse microbial community.

Signal crosstalk within biological communication networks is common, and such crosstalk can have unexpected consequences for decision making in hetero...

Exoskeletons for Personal Use After Spinal Cord Injury.

Before the development of robotic exoskeletons, mobility options beyond a wheelchair were very limited for most people lacking leg movement due to spi...

Intelligent prediction of kinetic parameters during cutting manoeuvres.

Due to its capabilities in analysing injury risk, the ability to analyse an athlete's ground reaction force and joint moments is of high interest in s...