Sports Medicine

MocapMe: DeepLabCut-Enhanced Neural Network for Enhanced Markerless Stability in Sit-to-Stand Motion Capture.

This study examined the efficacy of an optimized DeepLabCut (DLC) model in motion capture, with a particular focus on the sit-to-stand (STS) movement, which is crucial for assessing the functional capacity in elderly and postoperative patients. This research uniquely compared the performance of this optimized DLC model, which was trained using 'filtered' estimates from the widely used OpenPose (OP...

Effectiveness of Intelligent Control Strategies in Robot-Assisted Rehabilitation-A Systematic Review.

This review aims to provide a systematic analysis of the literature focused on the use of intelligent control systems in robotics for physical rehabilitation, identifying trends in recent research and comparing the effectiveness of intelligence used in control, with the aim of determining important factors in robot-assisted rehabilitation and how intelligent controller design can improve them. Sev...

Hspb1 and Lgals3 in spinal neurons are closely associated with autophagy following excitotoxicity based on machine learning algorithms.

Excitotoxicity represents the primary cause of neuronal death following spinal cord injury (SCI). While autophagy plays a critical and intricate role ...

Using machine learning to discover traumatic brain injury patient phenotypes: national concussion surveillance system Pilot.

OBJECTIVE: The objective is to determine whether unsupervised machine learning identifies traumatic brain injury (TBI) phenotypes with unique clinical...

A novel multi-task machine learning classifier for rare disease patterning using cardiac strain imaging data.

To provide accurate predictions, current machine learning-based solutions require large, manually labeled training datasets. We implement persistent h...

A Review of Artificial Intelligence in Breast Imaging.

With the increasing dominance of artificial intelligence (AI) techniques, the important prospects for their application have extended to various medic...

A Siamese Convolutional Neural Network for Identifying Mild Traumatic Brain Injury and Predicting Recovery.

Timely diagnosis of mild traumatic brain injury (mTBI) remains challenging due to the rapid recovery of acute symptoms and the absence of evidence of ...

Collaborative hunting in artificial agents with deep reinforcement learning.

Collaborative hunting, in which predators play different and complementary roles to capture prey, has been traditionally believed to be an advanced hu...

Enhanced biodegradation of phenol under Cr(VI) stress by microbial collaboration and potential application of machine learning for phenol biodegradation.

Cr(VI) and phenol commonly coexist in wastewater, posing a great threat to the environment and human health. However, it is still a challenge for micr...

Source Tracing of Kidney Injury via the Multispectral Fingerprint Identified by Machine Learning-Driven Surface-Enhanced Raman Spectroscopic Analysis.

Early diagnosis of drug-induced kidney injury (DIKI) is essential for clinical treatment and intervention. However, developing a reliable method to tr...

Rehabilitation Assessment System for Stroke Patients Based on Fusion-Type Optoelectronic Plethysmography Device and Multi-Modality Fusion Model: Design and Validation.

This study aimed to propose a portable and intelligent rehabilitation evaluation system for digital stroke-patient rehabilitation assessment. Specific...

Estimation of Shoulder Joint Rotation Angle Using Tablet Device and Pose Estimation Artificial Intelligence Model.

Traditionally, angle measurements have been performed using a goniometer, but the complex motion of shoulder movement has made these measurements intr...

Feasibility study of rehabilitation for cardiac patients aided by an artificial intelligence web-based programme: a randomised controlled trial (RECAP trial)-a study protocol.

INTRODUCTION: Cardiac rehabilitation (CR) delivered by rehabilitation specialists in a healthcare setting is effective in improving functional capacit...

A Case Report of Becker Muscular Dystrophy and Stroke Who Successfully Regained Mobility With Robot-Assisted Gait Training.

A 30-yr-old patient with Becker muscular dystrophy presented with stroke. Background issues of proximal weakness, dilated cardiomyopathy, and reduced ...

Identification and Connectomic Profiling of Concussion Using Bayesian Machine Learning.

Accurate early diagnosis of concussion is useful to prevent sequelae and improve neurocognitive outcomes. Early after head impact, concussion diagnosi...

Care-receivers with physical disabilities' perceptions on having humanoid assistive robots as assistants: a qualitative study.

BACKGROUND: People with physical disabilities due to disease or injury face barriers to their daily activities and participation in society. Many depe...

Age and medial compartmental OA were important predictors of the lateral compartmental OA in the discoid lateral meniscus: Analysis using machine learning approach.

PURPOSE: The objective of this study was to develop a machine learning model that would predict lateral compartment osteoarthritis (OA) in the discoid...

Microscopic computed tomography with AI-CNN-powered image analysis: the path to phenotype bleomycin-induced lung injury.

Bleomycin (BLM)-induced lung injury in mice is a valuable model for investigating the molecular mechanisms that drive inflammation and fibrosis and fo...

Multivariate analysis of the kinematics of an upper limb rehabilitation robot.

The purpose of this work is to present a multivariate analysis of the kinematics of an upper limb rehabilitation robot. Comparing multiple concepts o...

Exploring Human-Exoskeleton Interaction Dynamics: An In-Depth Analysis of Knee Flexion-Extension Performance across Varied Robot Assistance-Resistance Configurations.

Knee rehabilitation therapy after trauma or neuromotor diseases is fundamental to restore the joint functions as best as possible, exoskeleton robots ...