Sports Medicine

Artificial Intelligence in rehabilitation: A narrative review on advancing patient care.

Artificial Intelligence (AI) is revolutionizing rehabilitation by enabling data-driven, personalized, and effective patient care. AI systems analyze patterns, predict outcomes, and adapt treatments to individual needs, empowering clinicians to deliver more targeted and responsive interventions. This review explores AI's role in rehabilitation, focusing on its applications in personalized care, out...

Estimating oxygen uptake in simulated team sports using machine learning models and wearable sensor data: A pilot study.

Accurate assessment of training status in team sports is crucial for optimising performance and reducing injury risk. This pilot study investigates the feasibility of using machine learning (ML) models to estimate oxygen uptake (VO2) with wearable sensors during team sports activities. Six healthy male team sports athletes participated in the study. Data were collected using inertial measurement u...

Integrative neurorehabilitation using brain-computer interface: From motor function to mental health after stroke.

Stroke remains a leading cause of mortality and long-term disability worldwide, frequently resulting in impairments in motor control, cognition, and e...

Comparing machine learning models for predicting preoperative DVT incidence in elderly hypertensive patients with hip fractures: a retrospective analysis.

Hip fractures in the elderly present a significant public health challenge globally, especially among patients with hypertension, who are at an increa...

Achieving precision assessment of functional clinical scores for upper extremity using IMU-Based wearable devices and deep learning methods.

Stroke is a serious cerebrovascular disease, and rehabilitation following the acute phase is particularly crucial. Not all rehabilitation outcomes are...

An 8-Micrometer-Thick Film Strain Sensor with Conformal 3D Microstructure for Accurate Detection of Body Motion and Air Leakage.

Elastomer-based resistive super-thin film strain sensors show great application potentials in electronic skins, human-machine interaction systems, wea...

Review of sEMG for Exoskeleton Robots: Motion Intention Recognition Techniques and Applications.

The global aging trend is becoming increasingly severe, and the demand for life assistance and medical rehabilitation for frail and disabled elderly p...

Utilizing machine learning and geographic analysis to improve Post-crash traffic injury management and emergency response systems.

Traffic injuries are a major public health concern globally. This study uses machine learning (ML) and geographic analysis to analyse road traffic fat...

Exploring cortical excitability in children with cerebral palsy through lower limb robot training based on MI-BCI.

This study aims to compare brain activity differences under the motor imagery-brain-computer interface (MI-BCI), motor imagery (MI), and resting (REST...

The role of artificial intelligence in predicting injured structures based on clinical images of lacerations in the volar aspect of the hand and forearm.

INTRODUCTION: Recently introduced image processing capabilities of AI models, which are accessible to a broad audience, may contribute to progress in ...

Healthcare practitioners and robotic-assisted rehabilitation: understanding needs and barriers.

BACKGROUNDS: In recent years, numerous robotic devices, together with allied technologies, have been developed to support rehabilitation, both in rese...

Systematic review of AI/ML applications in multi-domain robotic rehabilitation: trends, gaps, and future directions.

Robotic technology is expected to transform rehabilitation settings, by providing precise, repetitive, and task-specific interventions, thereby potent...

Innovative diagnostic framework for shoulder instability: a narrative review on machine learning-enhanced scapular dyskinesis assessment in sports injuries.

A common shoulder problem that significantly detracts from patients' quality of life is shoulder instability (SI). Abnormal scapular positioning and m...

A muscle synergy-based method to improve robot-assisted movements.

There is increasing interest in using assistive robotic devices to support motor re-learning and recovery in individuals with neurological impairments...

Method of Forearm Muscles 3D Modeling Using Robotic Ultrasound Scanning.

The accurate assessment of muscle morphology and function is crucial for medical diagnostics, rehabilitation, and biomechanical research. This study p...

An innovative model based on machine learning and fuzzy logic for tracking lower limb exercises in stroke patients.

Rehabilitation after a stroke is vital for regaining functional abilities. However, a shortage of rehabilitation professionals leads to many patients ...

Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques.

Ventilator-associated pneumonia significantly increases morbidity, mortality, and healthcare costs among patients with traumatic brain injury. Accurat...

Forecasting motion trajectories of elbow and knee joints during infant crawling based on long-short-term memory (LSTM) networks.

BACKGROUND: Hands-and-knees crawling is a promising rehabilitation intervention for infants with motor impairments, while research on assistive crawli...

Digital Technologies and Artificial Intelligence in Cardiac Rehabilitation: A Narrative Review.

PURPOSE: This review explores the role and impact of digital technology in cardiac rehabilitation (CR), assessing its potential to enhance patient out...

A comparative study using response surface methodology and artificial neural network for modeling the bio-reduction of hexavalent chromium (Cr⁶⁺) by immobilized cells of Paenibacillus taichungensis strain MAHA in an alginate-gellan gum matrix.

Chromium (Cr⁶⁺) waste poses a hazard as it leads to imbalanced ecosystems and severe health issues. Although, it is widely associated with many indust...