AIMC Topic: Knee Joint
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Task-agnostic exoskeleton control via biological joint moment estimation.
Nature
Nov 13, 2024
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...
Acoustical features as knee health biomarkers: A critical analysis.
Artificial intelligence in medicine
Nov 10, 2024
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...
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
Nov 6, 2024
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...
Optimizing knee osteoarthritis severity prediction on MRI images using deep stacking ensemble technique.
Scientific reports
Nov 5, 2024
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...
Uncertainty-Aware Deep Learning Characterization of Knee Radiographs for Large-Scale Registry Creation.
The Journal of arthroplasty
Oct 29, 2024
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...
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
Oct 24, 2024
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...
MRI deep learning models for assisted diagnosis of knee pathologies: a systematic review.
European radiology
Oct 18, 2024
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...
A Robotic Clamped-Kinematic System to Study Knee Ligament Injury.
Annals of biomedical engineering
Oct 2, 2024
Knee ligament injury is among the most common sports injuries and is associated with long recovery periods and low return-to-sport rates. Unfortunately, the mechanics of ligament injury are difficult to study in vivo, and computational studies provid...
Recurrent Neural Network Enabled Continuous Motion Estimation of Lower Limb Joints From Incomplete sEMG Signals.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 27, 2024
Decoding continuous human motion from surface electromyography (sEMG) in advance is crucial for improving the intelligence of exoskeleton robots. However, incomplete sEMG signals are prevalent on account of unstable data transmission, sensor malfunct...
High accuracy in lower limb alignment analysis using convolutional neural networks, with improvements needed for joint-level metrics.
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Sep 22, 2024
PURPOSE: Evaluation of long-leg standing radiographs (LSR) is a standardised procedure for analysis of primary or secondary deformities of the lower limbs. Deep-learning convolutional neural networks (CNN) offer the potential to enhance radiological ...
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