AIMC Topic: Knee
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Performance of deep-learning models incorporating knee alignment information for predicting ground reaction force during walking.
Biomedical engineering online
Jun 24, 2025
BACKGROUND: Wearable sensors combined with deep-learning models are increasingly being used to predict biomechanical variables. Researchers have focused on either simple neural networks or complex pretrained models with multiple layers. In addition, ...
Classification of Grades of Subchondral Sclerosis from Knee Radiographic Images Using Artificial Intelligence.
Sensors (Basel, Switzerland)
Apr 17, 2025
Osteoarthritis (OA) is the most common joint disease, affecting over 300 million people worldwide. Subchondral sclerosis is a key indicator of OA. Currently, the diagnosis of subchondral sclerosis is primarily based on radiographic images; however, r...
Power-free knee rehabilitation robot for home-based isokinetic training.
Nature communications
Mar 8, 2025
Robot-assisted isokinetic training has been widely adopted for knee rehabilitation. However, existing rehabilitation facilities are often heavy, bulky, and extremely energy-consuming, which limits the rehabilitation opportunities only at designated h...
Development of a Wearable Sleeve-Based System Combining Polymer Optical Fiber Sensors and an LSTM Network for Estimating Knee Kinematics.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Feb 13, 2025
This study presents a novel wearable solution integrating Polymer Optical Fiber (POF) sensors into a knee sleeve to monitor knee flexion/extension (F/E) patterns during walking. POF sensors offer advantages such as flexibility, light weight, and robu...
Finding the needle in the haystack of isokinetic knee data: Random Forest modelling improves information about ACLR-related deficiencies.
Journal of sports sciences
Dec 22, 2024
The difficulties of rehabilitation after anterior cruciate ligament (ACL) injuries, subsequent return-to-sport (RTS) let alone achieving pre-injury performance, are well known. Isokinetic testing is often used to assess strength capacities during tha...
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...
Fourier Convolution Block with global receptive field for MRI reconstruction.
Medical image analysis
Sep 20, 2024
Reconstructing images from under-sampled Magnetic Resonance Imaging (MRI) signals significantly reduces scan time and improves clinical practice. However, Convolutional Neural Network (CNN)-based methods, while demonstrating great performance in MRI ...
Joint [Formula: see text] and Image Reconstruction in Low-Field MRI by Physics-Informed Deep-Learning.
IEEE transactions on bio-medical engineering
Sep 19, 2024
OBJECTIVE: We present a model-based image reconstruction approach based on unrolled neural networks which corrects for image distortion and noise in low-field ( B ∼ 50 mT) MRI.
Learning co-plane attention across MRI sequences for diagnosing twelve types of knee abnormalities.
Nature communications
Sep 2, 2024
Multi-sequence magnetic resonance imaging is crucial in accurately identifying knee abnormalities but requires substantial expertise from radiologists to interpret. Here, we introduce a deep learning model incorporating co-plane attention across imag...
Automatic quality assessment of knee radiographs using knowledge graphs and convolutional neural networks.
Medical physics
Jul 17, 2024
BACKGROUND: X-ray radiography is a widely used imaging technique worldwide, and its image quality directly affects diagnostic accuracy. Therefore, X-ray image quality control (QC) is essential. However, subjectively assessing image quality is ineffic...
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