AIMC Topic: Hip Joint

Clear Filters Showing 31 to 40 of 95 articles

Who Are the Anatomic Outliers Undergoing Total Knee Arthroplasty? A Computed Tomography-Based Analysis of the Hip-Knee-Ankle Axis Across 1,352 Preoperative Computed Tomographies Using a Deep Learning and Computer Vision-Based Pipeline.

The Journal of arthroplasty Mar 27, 2024
BACKGROUND: Dissatisfaction after total knee arthroplasty (TKA) ranges from 15 to 30%. While patient selection may be partially responsible, morphological and reconstructive challenges may be determinants. Preoperative computed tomography (CT) scans ...
Aged Aged, 80 and over Cross-Sectional Studies Humans Tomography, X-Ray Computed Female Knee Joint Arthroplasty, Replacement, Knee Hip Joint Male Middle Aged Deep Learning Ankle Joint
View on PubMed DOI

Hip contact forces can be predicted with a neural network using only synthesised key points and electromyography in people with hip osteoarthritis.

Osteoarthritis and cartilage Mar 3, 2024
OBJECTIVE: To develop and validate a neural network to estimate hip contact forces (HCF), and lower body kinematics and kinetics during walking in individuals with hip osteoarthritis (OA) using synthesised anatomical key points and electromyography. ...
Hip Joint Male Osteoarthritis, Hip Middle Aged Weight-Bearing Muscle, Skeletal Female Electromyography Aged Walking Humans Biomechanical Phenomena Neural Networks, Computer Gait
View on PubMed DOI

Machine learning-based prediction of hip joint moment in healthy subjects, patients and post-operative subjects.

Computer methods in biomechanics and biomedical engineering Feb 8, 2024
The application of machine learning in the field of motion capture research is growing rapidly. The purpose of the study is to implement a long-short term memory (LSTM) model able to predict sagittal plane hip joint moment (HJM) across three distinct...
Humans Machine Learning Female Middle Aged Postoperative Period Hip Joint Adult Biomechanical Phenomena Male
View on PubMed DOI

Automated digital templating of component sizing is accurate in robotic total hip arthroplasty when compared to predicate software.

Medical engineering & physics Jan 10, 2024
Accurate pre-operative templating of prosthesis components is an essential factor in successful total hip arthroplasty (THA), including robotically-assisted THA (RA-THA) techniques. We sought to validate the accuracy of a novel, robotic-optimized THA...
Robotics Robotic Surgical Procedures Hip Joint Arthroplasty, Replacement, Hip Preoperative Care Hip Prosthesis Retrospective Studies Reproducibility of Results Acetabulum Humans Software
View on PubMed DOI

Deep learning-based workflow for hip joint morphometric parameter measurement from CT images.

Physics in medicine and biology Nov 6, 2023
Precise hip joint morphometry measurement from CT images is crucial for successful preoperative arthroplasty planning and biomechanical simulations. Although deep learning approaches have been applied to clinical bone surgery planning, there is still...
Tomography, X-Ray Computed Deep Learning Hip Joint Workflow Arthroplasty, Replacement, Hip Hip Prosthesis
View on PubMed DOI

Effect of hip abduction assistance on metabolic cost and balance during human walking.

Science robotics Oct 25, 2023
The use of wearable robots to provide walking assistance has rapidly grown over the past decade, with notable advances made in robot design and control methods toward reducing physical effort while performing an activity. The reduction in walking eff...
Walking Gait Hip Joint Humans Biomechanical Phenomena Robotics
View on PubMed DOI

THA-Net: A Deep Learning Solution for Next-Generation Templating and Patient-specific Surgical Execution.

The Journal of arthroplasty Aug 22, 2023
BACKGROUND: This study introduces THA-Net, a deep learning inpainting algorithm for simulating postoperative total hip arthroplasty (THA) radiographs from a single preoperative pelvis radiograph input, while being able to generate predictions either ...
Retrospective Studies Deep Learning Radiography Hip Joint Arthroplasty, Replacement, Hip Hip Prosthesis Humans
View on PubMed DOI

Precise acetabular positioning, discrepancy in leg length, and hip offset using a new seven-axis robot-assisted total hip arthroplasty system requires no learning curve: a retrospective study.

Journal of orthopaedic surgery and research Mar 24, 2023
OBJECTIVE: The purpose of the present study was to determine the learning curve for a novel seven-axis robot-assisted total hip arthroplasty (RA-THA) system, and to explore whether it was able to provide greater accuracy in acetabular cup positioning...
Leg Hip Prosthesis Male Acetabulum Humans Hip Joint Robotics Arthroplasty, Replacement, Hip Retrospective Studies Female
View on PubMed DOI

Quantitative Gait Feature Assessment on Two-Dimensional Body Axis Projection Planes Converted from Three-Dimensional Coordinates Estimated with a Deep Learning Smartphone App.

Sensors (Basel, Switzerland) Jan 5, 2023
To assess pathological gaits quantitatively, three-dimensional coordinates estimated with a deep learning model were converted into body axis plane projections. First, 15 healthy volunteers performed four gait patterns; that is, normal, shuffling, sh...
Humans Knee Joint Aged Gait Hip Joint Biomechanical Phenomena Deep Learning Mobile Applications
View on PubMed DOI

John Charnley Award: Deep Learning Prediction of Hip Joint Center on Standard Pelvis Radiographs.

The Journal of arthroplasty Mar 16, 2022
BACKGROUND: Accurate hip joint center (HJC) determination is critical for preoperative planning, intraoperative execution, clinical outcomes after total hip arthroplasty, and commonly used classification systems in primary and revision hip replacemen...
Pelvis Hip Joint Awards and Prizes Biomechanical Phenomena Arthroplasty, Replacement, Hip Humans Male Female Deep Learning
View on PubMed DOI
Popular Topics
Recent Journals