AIMC Topic: Knee Joint

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A method to accurately estimate the muscular torques of human wearing exoskeletons by torque sensors.

Sensors (Basel, Switzerland)
In exoskeletal robots, the quantification of the user's muscular effort is important to recognize the user's motion intentions and evaluate motor abilities. In this paper, we attempt to estimate users' muscular efforts accurately using joint torque s...

Arthroscopy-validated diagnostic performance of sub-5-min deep learning super-resolution 3T knee MRI in children and adolescents.

Skeletal radiology
OBJECTIVE: This study aims to determine the diagnostic performance of sub-5-min combined sixfold parallel imaging (PIx3)-simultaneous multislice (SMSx2)-accelerated deep learning (DL) super-resolution 3T knee MRI in children and adolescents.

Influence of Robotic Versus Manual Technology for Achieving Sagittal Targets in Total Knee Arthroplasty Using a Cruciate-Retaining and Medial-Stabilized Implant.

The Journal of arthroplasty
BACKGROUND: Most of the focus regarding total knee arthroplasty (TKA) implant positioning and alignment has been centered on the coronal plane. Posterior condylar offset (PCO) and tibial slope (TS) are sagittal parameters that are measured on radiogr...

HSGDNet: Hybrid Synthetic-Data-Guided Deep Learning With NLS Refinement for Fast Multi-Component T1ρ Knee Mapping.

NMR in biomedicine
Multi-component T1ρ mapping of the knee joint using nonlinear least squares (NLS)-based methods is usually a computationally intensive task, limiting its application to only a few voxels in the knee joint. Deep learning (DL) is a computationally fast...

Automated quantitative analysis of peri-articular bone microarchitecture in HR-pQCT knee images.

Computer methods and programs in biomedicine
UNLABELLED: Applying HR-pQCT to image the knee necessitates the development and validation of novel image analysis workflows. Here, we present and validate the first automated workflow for in vivo quantitative assessment of peri-articular bone densit...

An AI system for continuous knee osteoarthritis severity grading: An anomaly detection inspired approach with few labels.

Artificial intelligence in medicine
The diagnostic accuracy and subjectivity of existing Knee Osteoarthritis (OA) ordinal grading systems has been a subject of on-going debate and concern. Existing automated solutions are trained to emulate these imperfect systems, whilst also being re...

Age and sex-specific differences of the intrafemoral and intratibial morphology using the Citak classification in patients undergoing total knee arthroplasty.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: Unlike established knee phenotype classifications, the recently introduced Citak classifications describe the intrafemoral and intratibial knee morphology. The aim of this study was to evaluate the distribution of Citak types A, B and C of t...

Predicting Knee Osteoarthritis Severity from Radiographic Predictors: Data from the Osteoarthritis Initiative.

Annals of biomedical engineering
PURPOSE: In knee osteoarthritis (KOA) treatment, preventive measures to reduce its onset risk are a key factor. Among individuals with radiographically healthy knees, however, future knee joint integrity and condition cannot be predicted by clinicall...

A Modular, Mechanical Knee Model for the Development and Validation of Robotic Testing Methodologies.

Journal of biomechanical engineering
Six-degree-of-freedom robotic testing is used to gain insight into knee function by measuring the biomechanics of cadaveric knees. However, it can be challenging to use cadaveric knees to validate robotic testing methodologies and to compare methodol...