BACKGROUND: Optimal implant position and alignment remains a controversial, yet critical topic in primary total knee arthroplasty (TKA). Future study of ideal implant position will require the ability to efficiently measure component positions at sca...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
40031675
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...
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...
Background Deep learning (DL) methods can improve accelerated MRI but require validation against an independent reference standard to ensure robustness and accuracy. Purpose To validate the diagnostic performance of twofold-simultaneous-multislice (S...
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...
Gait analysis is crucial for identifying functional deviations from the normal gait cycle and is essential for the individualized treatment of motor disorders such as cerebral palsy (CP). The primary contribution of this study is the introduction of ...
Knee arthritis is a prevalent joint condition that affects many people worldwide. Early detection and appropriate treatment are essential to slow the disease's progression and enhance patients' quality of life. In this study, various machine learning...
Knee Osteoarthritis (KOA), a leading cause of disability worldwide, is challenging to detect early due to subtle radiographic indicators. Diverse, extensive datasets are needed but are challenging to compile because of privacy, data collection limita...
Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
39902572
Generative deep learning has emerged as a promising data augmentation technique in recent years. This approach becomes particularly valuable in areas such as motion analysis, where it is challenging to collect substantial amounts of data. The objecti...
Legged robots, designed to emulate human functions, have greatly influenced numerous sectors. However, the focus on continuously improving the joint motors and control systems of existing legged robots not only increases costs and complicates mainten...