Sports Medicine

Preliminary Results of Neuromorphic Controller Design and a Parkinson's Disease Dataset Building for Closed-Loop Deep Brain Stimulation

Parkinson's Disease afflicts millions of individuals globally. Emerging as a promising brain rehabilitation therapy for Parkinson's Disease, Closed-loop Deep Brain Stimulation (CL-DBS) aims to alleviate motor symptoms. The CL-DBS system comprises an implanted battery-powered medical device in the chest that sends stimulation signals to the brains of patients. These electrical stimulation signals...

Optimizing Concussion Care Seeking: Using Machine Learning to Predict Delayed Concussion Reporting.

BACKGROUND: Early medical attention after concussion may minimize symptom duration and burden; however, many concussions are undiagnosed or have a delay in diagnosis after injury. Many concussion symptoms (eg, headache, dizziness) are not visible, meaning that early identification is often contingent on individuals reporting their injury to medical staff. A fundamental understanding of the types a...

An Efficient Deep Transfer Learning Network for Characterization of Stroke Patients' Motor Execution from Multi-Channel EEG-Recordings.

Recent advances in stroke rehabilitation technology have been focused on developing Intelligent Rehabilitation Robots (IRR) that can effectively engag...

Classification of Upper Limb Movements based on a LSTM Model in Aquatic Rehabilitation.

The objectives of this study were to improve aquatic rehabilitation through the utilization of LSTM model based activity classification by (1) identif...

Design and Development of 8-DoF Forearm Rehabilitation Device.

Robotic systems for rehabilitating forearm have been an active area of research. A majority of the daily living activities require the use of the fore...

Multidimensional feature analysis shows stratification in robotic-motor-training gains based on the level of pre-training motor impairment in stroke.

Stroke involves heterogeneity in injury and ongoing endogenous recovery, which are seldom stratified before testing post-stroke robot assisted motor t...

Unsupervised Gait Assessments of Stroke Patients Using a Smartphone and Machine Learning.

Home-based rehabilitation is a trend of post-stroke lower limb rehabilitation, aimed at a long-term and higher dose of therapy. Unsupervised gait asse...

Deep Left Ventricular Motion Estimation Methods in Echocardiography: A Comparative Study.

Motion estimation in echocardiography is critical when assessing heart function and calculating myocardial deformation indices. Nevertheless, there ar...

Preliminary Experimental Validation of a Cable-Driven Joint System for Custom Orthoses.

Robot-assisted gait training has the potential to enhance gait therapy for children with mobility impairments. Robotic orthoses are designed to improv...

A Resistance-Free Sit-To-Stand Rehabilitative System Incorporated with Multi-Sensory Feedback.

Robotic rehabilitative systems have been an active area of research for all movements, including Sit to Stand (STS). STS is an important movement for ...

Computational Analysis of Mechanical Interactions between a Soft Robotic Device and a Skin-Muscle Phantom for Mechanotherapy.

Studying the soft robot-tissue mechanical interaction in muscle stimulation devices poses a significant challenge due to the complex behavior of the m...

Remote Motor Rehabilitation: EMG-IMU based Deep Learning Model Improves the Estimate of Wrist Kinematics.

Technology for motor rehabilitation faces challenges in uncontrolled settings, such as at home. In these real-world scenarios, robust signals like ele...

Walking Speed and Uncertainty Estimation Using Mixture Density Networks for Dynamic Ambulatory Environments.

Walking speed, often considered a representative indicator of activity levels, becomes notably reduced as muscle strength and cardiovascular function ...

Innovative Approaches to Gender Classification through Unsupervised Machine Learning and Multi-Activity Fusion.

In the last decade, gender recognition has garnered significant attention for its diverse applications in healthcare, sports, rehabilitation, and wear...

Effects of training with a rehabilitation device (Rebless®) on upper limb function in patients with chronic stroke: A randomized controlled trial.

BACKGROUND: Upper limb dysfunction is one of the most common sequelae of stroke and robotic therapy is considered one of the promising methods for upp...

Unsupervised Machine Learning in Countermovement Jump and Isometric Mid-Thigh Pull Performance Produces Distinct Combat and Physical Fitness Clusters in Male and Female U.S. Marine Corps Recruits.

INTRODUCTION: Several challenges face the U.S. Marine Corps (USMC) and other services in their efforts to design recruit training to augment warfighte...

Prediction of gait recovery using machine learning algorithms in patients with spinal cord injury.

With advances in artificial intelligence, machine learning (ML) has been widely applied to predict functional outcomes in clinical medicine. However, ...

[Minimally invasive intelligent innovative technologies in foot and ankle surgery: development status and prospects].

The rapid development of technology has ushered in a new era of minimally invasive and intelligent surgery.Minimally invasive surgeries, such as small...

Efficacy of Daoyin combined with lower limb robot as a comprehensive rehabilitation intervention for stroke patients: a randomized controlled trial.

OBJECTIVE: To assess the effectiveness of a comprehensive rehabilitation approach combining Traditional Chinese Medicine Daoyin with lower limb roboti...

Automated stratification of trauma injury severity across multiple body regions using multi-modal, multi-class machine learning models.

OBJECTIVE: The timely stratification of trauma injury severity can enhance the quality of trauma care but it requires intense manual annotation from c...