Cornell University
Library
Cornell UniversityLibrary

eCommons

Help
Log In(current)
  1. Home
  2. Cornell University Graduate School
  3. Cornell Theses and Dissertations
  4. HIGH STRAIN RATE MEASUREMENTS FOR PREDICTING BRAIN TRAUMA

HIGH STRAIN RATE MEASUREMENTS FOR PREDICTING BRAIN TRAUMA

File(s)
Tovar_cornell_0058O_12588.pdf (13.65 MB)
No Access Until
2026-03-09
Permanent Link(s)
https://doi.org/10.7298/wqdw-8b67
https://hdl.handle.net/1813/120678
Collections
Cornell Theses and Dissertations
Author
Tovar, Mariana
Abstract

Soft, high-speed sensors are crucial for real-time detection of mechanical de-formation in brain-like materials, particularly in studying mild traumatic brain injury (mTBI). This work presents the design, fabrication, and validation of stretchable optical fiber sensors using thermoplastic polyurethane waveguides paired with infrared optoelectronics. A repeatable process was established, pro- ducing sensors with consistent mechanical stiffness and electrical sensitivity un- der tensile loads. Dynamic testing was performed using ballistic and blunt im- pacts in hydrogel, silicone, and preserved sheep brain tissue. Results confirmed millisecond-scale responsiveness and sensitivity to both local deformation and impact propagation. Sensor performance under compressive and constrained conditions was also evaluated, revealing limitations due to pre-strain and ma- terial swelling. A localization framework based on LASSO regression was de- veloped and validated on a 2D sensor matrix. While complete 3D localization was not implemented, the system demonstrated feasibility for integration into future diagnostic platforms for mTBI detection and soft-tissue impact sensing.

Description
71 pages
Date Issued
2025-08
Committee Chair
Shepherd, Robert
Committee Member
Nunez, Cara
Degree Discipline
Mechanical Engineering
Degree Name
M.S., Mechanical Engineering
Degree Level
Master of Science
Rights
Attribution 4.0 International
Rights URI
https://creativecommons.org/licenses/by/4.0/
Type
dissertation or thesis

Site Statistics | Help

About eCommons | Policies | Terms of use | Contact Us

copyright © 2002-2026 Cornell University Library | Privacy | Web Accessibility Assistance