AIMC Topic: Hip Joint
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Development of a Deep Learning Model for Automating Implant Position in Total Hip Arthroplasty.
The Journal of arthroplasty
Jan 27, 2025
BACKGROUND: Novel methods for annotating antero-posterior pelvis radiographs and fluoroscopic images with deep-learning models have recently been developed. However, their clinical use has been limited. Therefore, the purpose of this study was to dev...
Artificial neural networks' estimations of lower-limb kinetics in sidestepping: Comparison of full-body vs. lower-body landmark sets.
Journal of biomechanics
Jan 27, 2025
Artificial neural networks (ANNs) offers potential for obtaining kinetics in non-laboratory. This study compared the estimation performance for ground reaction forces (GRF) and lower-limb joint moments during sidestepping between ANNs fed with full-b...
Predicting lower body joint moments and electromyography signals using ground reaction forces during walking and running: An artificial neural network approach.
Gait & posture
Jan 21, 2025
BACKGROUND: This study leverages Artificial Neural Networks (ANNs) to predict lower limb joint moments and electromyography (EMG) signals from Ground Reaction Forces (GRF), providing a novel perspective on human gait analysis. This approach aims to e...
Robot-Aided Training of Propulsion: Effects of Torque Pulses Applied to the Hip and Knee Joint Under User-Driven Treadmill Control.
IEEE transactions on bio-medical engineering
Jan 15, 2025
OBJECTIVE: to establish whether torque pulses applied by an exoskeleton to the hip and knee joint modulate propulsion mechanics and whether changes in propulsion mechanics are sustained after exposure to torque pulses under user-driven treadmill cont...
Optimizing hip MRI: enhancing image quality and elevating inter-observer consistency using deep learning-powered reconstruction.
BMC medical imaging
Jan 13, 2025
BACKGROUND: Conventional hip joint MRI scans necessitate lengthy scan durations, posing challenges for patient comfort and clinical efficiency. Previously, accelerated imaging techniques were constrained by a trade-off between noise and resolution. L...
Validation of AI-driven measurements for hip morphology assessment.
European journal of radiology
Dec 31, 2024
RATIONALE AND OBJECTIVES: Accurate assessment of hip morphology is crucial for the diagnosis and management of hip pathologies. Traditional manual measurements are prone to mistakes and inter- and intra-reader variability. Artificial intelligence (AI...
Effect of wearable robot Bot Fit's hip joint-centered assist torque and voice coach on walking.
BMC musculoskeletal disorders
Dec 23, 2024
BACKGROUND: The main key to the 4th industrial era is robots, and wearable robots are incorporated into human healthcare. Samsung Electronics' Bot Fit is a hip joint-centered assistive robot that can induce walking posture and energetic walking exerc...
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
Nov 20, 2024
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 ...
Deep learning-based automated measurement of hip key angles and auxiliary diagnosis of developmental dysplasia of the hip.
BMC musculoskeletal disorders
Nov 13, 2024
OBJECTIVES: Anteroposterior pelvic radiographs remains the most widely employed method for diagnosing developmental dysplasia of the hip. This study aims to evaluate the accuracy of an artificial intelligence model in measuring angles in pelvic radio...
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...
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