Undergraduate Research Experience- Material Robotics Laboratory
I have spent the past year and a half as an undergraduate research assistant at Boston University's Material Robotics Lab. This lab specializes in the development, design, fabrication, and testing of surgical and soft robotics. The research combines Mechanical Engineering and Biomedical Engineering, and integrates commercial surgical instruments with innovative soft robotic improvements while collaborating with doctors and surgeons at Boston hospitals.
Read more on the lab site: https://sites.bu.edu/mrl/
Accomplishments & Publications
I have been awarded as a recipient of Boston University's UROP (Undergraduate Research Opportunity Program) funding twice, a stipend awarded to students based on successful applications and project proposals.
I have also been named a Clare Booth Luce Research Scholar in Summer 2020, a grant awarded to top female researchers in STEM.
Additionally, I have been a co-author on two publications, linked below. My role in these projects will be described in greater detail following.
A Soft Robotic Sleeve for Safer Colonoscopy Procedures: https://ieeexplore.ieee.org/document/9405477
A Soft Robot for Peripheral Lung Cancer Diagnosis and Therapy: https://www.liebertpub.com/doi/10.1089/soro.2020.0127
A Soft Robotic Sleeve for Safer Colonoscopy Procedures
Background
The colonoscopy procedure relies on manual navigation by the surgeon, and can cause tearing of the colon tissue, discomfort, and increased recovery time if there is too much force applied while navigating the zig zag cavity. The goal of the soft robotic skin is to wrap around commercial endoscopes, measure force inputs with optical waveguides, and inflate actuators to relieve stress against the colon if the force is too high.
Layout of the soft robotic skin with actuators and sensors, shape of colon and navigation with the colonoscope
Responsibility
Before Covid, I fabricated scaled-up models of the soft robotic skin using Ecoflex, Dragonskin, and Vytaflex (soft, compliant materials). The fabrication process involved pouring the elastomers in an aluminum mold machined with a CNC machine, removing air bubbles in a vacuum chamber, allowing the material to cure, and using a spin coater to spin coat a thin additional layer to the top of the skin. Additionally, I fabricated and tested the optical waveguide sensors by creating waveguide cores with Vytaflex and testing the optical sensor outputs by callibrating LEDs and photodiodes and collecting data with a Matlab script.
During COVID, I worked remotely modeling various aspects of the project in CAD including each layer of the soft skin itself, the scaled down mold, and the colon. Using these models along with the mechanical properties of the elastomers, colonoscope, and colon tissue, I learned how to perform Finite Element Analysis with Abaqus to analyze pressure inside the actuators, displacement of the actuators depending on the number and spacing of the actuators, and stress against the colon walls with and without actuators present. FEA results are shown in the figure below.
FEA data and visual results depicting actuator displacement after inflation, stress on colon walls, and stress on curved model of colon walls
Impact
The results from the FEA simulations were used to determine the best design for the skin (i.e. skin thickness, actuator number and placement) allowing for the most displacement during inflation and the most stress relief for the colon.
A Soft Robot for Peripheral Lung Cancer Diagnosis
Background
Lung cancer is difficult to find and diagnose due to its common location deep in the peripheral branches of the lung and the necessity of doing a biopsy on the tissue to receive a diagnosis. This soft robot allows for navigation deep into the lungs and has interventional capabilities.
Responsibility
Fabricated backup catheters, utilized the camera to navigate through a 3D printed model of the lung by selecting contours while collecting data regarding the pneumatic infusion rate and accuracy of the actuator position
Left: 3D model of lungs used to test navigation
Right: Camera snapshots, contours used to select new branch to navigate bronchoscope to
Impact
The results from the tests I conducted were informative for selecting the most accurate infusion rate of the catheter when deterring the tip to navigate to a new branch, and troubleshooting the device and software while navigating the lungs.