Natalie Nguyen

Major and Classification

Mechanical Engineering

Faculty Mentor

Veronica Eliasson, Ph.D., Viterbi School of Engineering


Viterbi School of Engineering

Research Gateway Project

“Quantifying neural network strain caused by stress waves from dynamic loading using HAMr (Highly Automated Mechanical Impactor) and the shadow moiré method”

Project Abstract

Protective gear against brain injury can be improved with a better understanding of the biological and mechanical response of the brain under dynamic loading. A new mechanism, HAMr, is designed to perform repeated blunt impact forces on in vitro neural networks under controlled conditions. The neural networks from mice are prepared in a nutrient bath within a petri dish. HAMr enables us to investigate the role that the stress wave plays in causing brain injury by isolating the stress wave component of dynamic loading. In addition, the shadow moiré method is to be used in conjunction with HAMr to quantify brain injury by producing light and dark fringes that indicate the strain deformation of the neural networks. To observe these fringes, a high-speed camera is used to record the deformation during the impact event. The scope of this research entails testing and verifying the capabilities of the shadow moiré setup under these circumstances. Future work includes improving upon this setup to use in conjunction with HAMr to provide clear results that will allow us to better quantify brain injury caused by stress waves in neural networks.