2017 ~ Present

A Digital Cure for Epilepsy

Goals

By predicting seizure before its onset, doctors could act preventively with actions that include stimulation treatment recently proposed. To facilitate that, scientists at Rice University and the University of Texas Health Science Center will work together to develop algorithms that will optimize the development of an implantable device. The device will deliver low-frequency electrical stimulation to the seizure on-set zone.

Issues Involved or Addressed

This project involves machine learning and embedded hardware development. We take EEG data sets from epilepsy patients and develop algorithms able to predict seizures based on previous data. We plan to develop algorithms that will be able to prevent the predicted seizures from occurring by selectively injecting electrical signals to suppress seizures, much as a pacemaker prevents heartbeat irregularity. We are also developing embedded hardware, ultimately an ASIC, that can be implanted in a patient much as a pacemaker would be today.

Methods and Technologies

  • Machine learning
  • Data Science
  • Electoencelography
  • IC Design
  • FPGA Design

Academic Majors of Interest

  • Electrical and Computer Engineering
  • Computer Science
  • BioEngineering
  • Computational and Applied Mathematics
  • Statistics
  • Psychology
  • BioSciences

Preferred Interests and Preparation

Interest in neuroengineering, data science, or computer engineering.
Relevant coursework in any of those fields.

Team Advisors

Behnaam Aazhang

Sponsor(s)