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Mechanical Phenomena

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Optimization and control of robotic vertebral plate grinding: Predictive modeling, parameter optimization, and fuzzy control strategies for minimizing bone damage in laminectomy procedures.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
During the robotic grinding of vertebral plates in high-risk laminectomy procedures, programmed operations may inadvertently induce force or temperature-related damage to the bone tissue. Therefore, it is imperative to explore a control methodology a...

Improving arterial stiffness prediction with machine learning utilizing hemodynamics and biomechanical features derived from phase contrast magnetic resonance imaging.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Arterial stiffness has emerged as a prominent marker of risk for cardiovascular diseases. Few studies are interested in predicting symptomatic or asymptomatic arterial stiffness from hemodynamics and biomechanics parameters. Machine learning models c...

Development of hybrid bionanocomposites of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) with zinc oxide and silicon-doped hydroxyapatite nanocrystals and machine learning for predicting dynamic mechanical properties.

International journal of biological macromolecules
The development of hybrid materials that integrate bioactive and antimicrobial properties within a biodegradable and biocompatible polymer matrix is a key focus in current biomedical research and applications. A significant research gap exists in the...

Super-fast and accurate nonlinear foot deformation Prediction using graph neural networks.

Journal of the mechanical behavior of biomedical materials
Recently, there has been a significant increase in the number of foot diseases, highlighting the importance of non-surgical treatments. Customized insoles, tailored to an individual's foot morphology, have emerged as a promising solution. However, th...

Learning soft tissue deformation from incremental simulations.

Medical physics
BACKGROUND: Surgical planning for orthognathic procedures demands swift and accurate biomechanical modeling of facial soft tissues. Efficient simulations are vital in the clinical pipeline, as surgeons may iterate through multiple plans. Biomechanica...

A bio-lattice deep learning framework for modeling discrete biological materials.

Journal of the mechanical behavior of biomedical materials
Biological tissues dynamically adapt their mechanical properties at the microscale in response to stimuli, often governed by discrete interacting mechanisms that dictate the material's behavior at the macroscopic scale. An approach to model the discr...

Simulation of a Free Boundary Cell Migration Model through Physics Informed Neural Networks.

Journal of the mechanical behavior of biomedical materials
Understanding the complexities of single-cell migration is facilitated by computational modeling, which provides important insights into the physiological processes that underlie migration mechanisms. This study developed a computational model for on...

Synthetic data generation in motion analysis: A generative deep learning framework.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
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...

Predicting ground reaction forces and center of pressures from kinematic data in crutch gait based on LSTM.

Medical engineering & physics
Crutches are of extensive applications in the field of rehabilitation. Comprehensively analyzing the ground reaction forces (GRFs) on both crutches and feet can evaluate the patients' walking function recovery. Given more force platforms are needed i...

Exploring the Influence of Feature Selection Methods on a Random Forest Model for Gait Time Series Prediction Using Inertial Measurement Units.

Journal of biomechanical engineering
Despite the increasing use of inertial measurement units (IMUs) and machine learning techniques for gait analysis, there remains a gap in which feature selection methods are best tailored for gait time series prediction. This study explores the impac...