Computational Validation of Functionally Graded 3D Printed Rib Fracture Fixation Implants

BME 450W: Biomedical Senior Design

Jan-May 2022

Sponsor: Penn State SHAPE Lab

Objective

Our sponsor tasked us with developing a pixel-tracking software that could perform digital image correlation (DIC) analysis on unfiltered video footage of 3D printed rib implants undergoing a four-point bend test and output specific material properties for the test samples in the videos.

Overcoming Challenges

Our sponsor wanted this programmed in Python. One week before the project start date, our only computer science team member dropped out, and none of the rest of us had any prior experience programming in Python. As a team, we used online resources and helped each other to learn Python and about digital image correlation. We programmed and tested multiple iterations of the software, developed an aesthetic and user-friendly graphic user interface, and constructed our own DIC setup to generate test input to validate the final software product.

My Role

As the designated team Project Lead, I maintained communication with our sponsor to ensure we were meeting their needs throughout the course of the project.
Along with two other team members, I designed a cost-effective 2D DIC setup and recorded sample deformation footage for use in testing and validating our image analysis software.
Contributed to testing, validating, and troubleshooting of various program iterations.