Biomedical Engineering and Bioengineering Commons^™

Predictive Behavior Of A Computational Foot/Ankle Model Through Artificial Neural Networks, Ruchi D. Chande, Rosalyn Hobson Hargraves, Norma Ortiz-Robinson, Jennifer S. Wayne

Biomedical Engineering Publications

Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue properties are implemented from literature data, when available. We sought to improve the predictive capability of a computational foot/ankle model by optimizing its ligament stiffness inputs using feedforward and radial basis function neural networks. While the former demonstrated better performance than the latter per mean square error, both networks provided reasonable stiffness predictions for implementation into the computational model.

Substrate Stiffness Controls Osteoblastic And Chondrocytic Differentiation Of Mesenchymal Stem Cells Without Exogenous Stimuli, Rene Olivares-Navarrete, Erin M. Lee, Kathryn Smith, Sharon L. Hyzy, Maryam Doroudi, Joseph K. Williams, Ken Gall, Barbara D. Boyan, Zvi Schwartz

Biomedical Engineering Publications

Stem cell fate has been linked to the mechanical properties of their underlying substrate, affecting mechanoreceptors and ultimately leading to downstream biological response. Studies have used polymers to mimic the stiffness of extracellular matrix as well as of individual tissues and shown mesenchymal stem cells (MSCs) could be directed along specific lineages. In this study, we examined the role of stiffness in MSC differentiation to two closely related cell phenotypes: osteoblast and chondrocyte. We prepared four methyl acrylate/methyl methacrylate (MA/MMA) polymer surfaces with elastic moduli ranging from 0.1 MPa to 310 MPa by altering monomer concentration. MSCs were cultured in …

Predictive Behavior Of A Computational Foot/Ankle Model Through Artificial Neural Networks, Ruchi D. Chande, Rosalyn Hobson Hargraves, Norma Ortiz-Robinson, Jennifer S. Wayne

Biomedical Engineering Publications

Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue properties are implemented from literature data, when available. We sought to improve the predictive capability of a computational foot/ankle model by optimizing its ligament stiffness inputs using feedforward and radial basis function neural networks. While the former demonstrated better performance than the latter per mean square error, both networks provided reasonable stiffness predictions for implementation into the computational model.

Aging Effects On Airflow Dynamics And Lung Function In Human Bronchioles, Jongwon Kim, Rebecca L. Heise, Angela M. Reynolds, Ramana M. Pidaparti

Biomedical Engineering Publications

Background and objective

The mortality rate for patients requiring mechanical ventilation is about 35% and this rate increases to about 53% for the elderly. In general, with increasing age, the dynamic lung function and respiratory mechanics are compromised, and several experiments are being conducted to estimate these changes and understand the underlying mechanisms to better treat elderly patients.

Materials and methods

Human tracheobronchial (G1 ~ G9), bronchioles (G10 ~ G22) and alveolar sacs (G23) geometric models were developed based on reported anatomical dimensions for a 50 and an 80-year-old subject. The aged model was developed by altering the geometry and …