AIMC Topic: Knee Joint
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Myoelectric control algorithm for robot-assisted therapy: a hardware-in-the-loop simulation study.
Biomedical engineering online
Jan 3, 2019
BACKGROUND: A direct blow to the knee is one way to injure the anterior cruciate ligament (ACL), e.g., during a football or traffic accident. Robot-assisted therapy (RAT) rehabilitation, simulating regular walking, improves walking and balance abilit...
Deep Learning for Musculoskeletal Force Prediction.
Annals of biomedical engineering
Dec 31, 2018
Musculoskeletal models permit the determination of internal forces acting during dynamic movement, which is clinically useful, but traditional methods may suffer from slowness and a need for extensive input data. Recently, there has been interest in ...
Total Knee Arthroplasty Is Safe and Successful in Patients With Klippel-Trénaunay Syndrome.
The Journal of arthroplasty
Dec 22, 2018
BACKGROUND: Klippel-Trénaunay syndrome (KTS) is a severe vascular malformation that can lead to hypertrophic osteoarthritis. Total knee arthroplasty (TKA) performed in extremities affected with KTS is challenging given the high-risk vascular consider...
Femoral Contact Forces in the Anterior Cruciate Ligament Deficient Knee: A Robotic Study.
Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
Nov 2, 2018
PURPOSE: To measure contact forces (CFs) at standardized locations representative of clinical articular cartilage defects on the medial and lateral femoral condyles during robotic tests with simulated weightbearing knee flexion.
Deep Learning Approach for Evaluating Knee MR Images: Achieving High Diagnostic Performance for Cartilage Lesion Detection.
Radiology
Jul 31, 2018
Purpose To determine the feasibility of using a deep learning approach to detect cartilage lesions (including cartilage softening, fibrillation, fissuring, focal defects, diffuse thinning due to cartilage degeneration, and acute cartilage injury) wit...
A CNN-SVM combined model for pattern recognition of knee motion using mechanomyography signals.
Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
Jul 26, 2018
The commonly used classifiers for pattern recognition of human motion, like backpropagation neural network (BPNN) and support vector machine (SVM), usually implement the classification by extracting some hand-crafted features from the human biologica...
Deep convolutional neural network for segmentation of knee joint anatomy.
Magnetic resonance in medicine
May 17, 2018
PURPOSE: To describe and evaluate a new segmentation method using deep convolutional neural network (CNN), 3D fully connected conditional random field (CRF), and 3D simplex deformable modeling to improve the efficiency and accuracy of knee joint tiss...
Effects of Proud Large Osteochondral Plugs on Contact Forces and Knee Kinematics: A Robotic Study.
The American journal of sports medicine
May 9, 2018
BACKGROUND: Osteochondral allograft (OCA) transplantation is used to treat large focal femoral condylar articular cartilage defects. A proud plug could affect graft survival by altering contact forces (CFs) and knee kinematics.
Predicting net joint moments during a weightlifting exercise with a neural network model.
Journal of biomechanics
Apr 25, 2018
The purpose of this study was to develop and train a Neural Network (NN) that uses barbell mass and motions to predict hip, knee, and ankle Net Joint Moments (NJM) during a weightlifting exercise. Seven weightlifters performed two cleans at 85% of th...
Use of 2D U-Net Convolutional Neural Networks for Automated Cartilage and Meniscus Segmentation of Knee MR Imaging Data to Determine Relaxometry and Morphometry.
Radiology
Mar 27, 2018
Purpose To analyze how automatic segmentation translates in accuracy and precision to morphology and relaxometry compared with manual segmentation and increases the speed and accuracy of the work flow that uses quantitative magnetic resonance (MR) im...
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