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Knee Joint

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Lower Limb Torque Prediction for Sit-To-Walk Strategies Using Long Short-Term Memory Neural Networks.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Joint torque prediction is crucial when investigating biomechanics, evaluating treatments, and designing powered assistive devices. Controllers in assistive technology require reference torque trajectories to set the level of assistance for a patient...

Machine learning is better than surgeons at assessing unicompartmental knee replacement radiographs.

The Knee
BACKGROUND: Poor results occasionally occur after unicompartmental knee replacement (UKR). It is often difficult, even for experienced surgeons, to determine why patients have poor outcomes from radiographs. The aim was to compare the ability of expe...

HKA-Net: clinically-adapted deep learning for automated measurement of hip-knee-ankle angle on lower limb radiography for knee osteoarthritis assessment.

Journal of orthopaedic surgery and research
BACKGROUND: Accurate measurement of the hip-knee-ankle (HKA) angle is essential for informed clinical decision-making in the management of knee osteoarthritis (OA). Knee OA is commonly associated with varus deformity, where the alignment of the knee ...

Acoustical features as knee health biomarkers: A critical analysis.

Artificial intelligence in medicine
Acoustical knee health assessment has long promised an alternative to clinically available medical imaging tools, but this modality has yet to be adopted in medical practice. The field is currently led by machine learning models processing acoustical...

Task-agnostic exoskeleton control via biological joint moment estimation.

Nature
Lower-limb exoskeletons have the potential to transform the way we move, but current state-of-the-art controllers cannot accommodate the rich set of possible human behaviours that range from cyclic and predictable to transitory and unstructured. We i...

Optimizing knee osteoarthritis severity prediction on MRI images using deep stacking ensemble technique.

Scientific reports
Knee osteoarthritis (KOA) represents a well-documented degenerative arthropathy prevalent among the elderly population. KOA is a persistent condition, also referred to as progressive joint Disease, stemming from the continual deterioration of cartila...

ShapeMed-Knee: A Dataset and Neural Shape Model Benchmark for Modeling 3D Femurs.

IEEE transactions on medical imaging
Analyzing anatomic shapes of tissues and organs is pivotal for accurate disease diagnostics and clinical decision-making. One prominent disease that depends on anatomic shape analysis is osteoarthritis, which affects 30 million Americans. To advance ...

Evaluation of a novel robotic testing method for stability and kinematics of total knee arthroplasty.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: This work developed a novel preclinical test of total knee replacements (TKRs) in order to explain TKR instability linked to patient dissatisfaction. It was hypothesized that stability tests on the isolated moving prostheses would provide no...

Uncertainty-Aware Deep Learning Characterization of Knee Radiographs for Large-Scale Registry Creation.

The Journal of arthroplasty
BACKGROUND: We present an automated image ingestion pipeline for a knee radiography registry, integrating a multilabel image-semantic classifier with conformal prediction-based uncertainty quantification and an object detection model for knee hardwar...

MRI deep learning models for assisted diagnosis of knee pathologies: a systematic review.

European radiology
OBJECTIVES: Despite showing encouraging outcomes, the precision of deep learning (DL) models using different convolutional neural networks (CNNs) for diagnosis remains under investigation. This systematic review aims to summarise the status of DL MRI...