Rice University Students Developing Technology to Help Treat Epilepsy

Funded by the National Science Foundation, their electrical stimulation device is designed to prevent seizures

23 June 2017

Epilepsy is one of the most common neurological diseases worldwide, with more than 50 million people suffering from recurrent seizures, according to the World Health Organization. Many patients do not respond well to medical treatments and often resort to invasive and dangerous procedures.

Students and faculty at Rice University in collaboration with faculty at The University of Texas Health and Science Center (UTHealth), both in Houston, are working on a device to assist epilepsy patients. IEEE Fellow Behnaam Aazhang and IEEE Member Gary Woods are the faculty advisors for the project, A Digital Cure for Epilepsy. It is funded by the National Science Foundation and the Helmsley Charitable Trust through a grant to the Georgia Institute of Technology, in Atlanta, which helped spearhead the project. The NSF originally provided a US $1 million grant and continues to support the project.

“We are developing a stimulation treatment—a minimally invasive implantable device that will deliver low-frequency electrical stimulation to the seizure onset zone, effectively preventing the seizure,” the team wrote on its website.

The technique stimulates the brain’s surface—which is safer and more reliable than treatments that require surgical removal of brain tissue, said the project’s initial report.

FUNCTION AND PERFORMANCE

Two parts make up the device: a chip inserted under the skull and electrodes placed on the brain, and in some cases, deep in brain tissues. The current solution, as precursor to a chip design, is a board that is 10 by 20 centimeters in size; the final chip will be just several millimeters, Aazhang says. Most implantation of the electrodes requires a craniotomy in which a rectangular electrode grid is surgically placed on the patient’s cortex, the region of the brain where epileptic activity occurs. Electrocorticography data is then used to monitor that area.

The device is able to predict the onset of a seizure up to two minutes in advance, thanks to the machine-learning algorithm the student design team developed in 2016 using patient data gathered by UTHealth.

The chip eventually will have a wireless link from the outside world that carries power and data, according to IEEE Student Member Marissa Levy. For now, the board resides outside the skull and requires a wired link. IEEE Student Member Sarah Hooper explains in the video above about the device that once the chip recognizes a seizure is about to happen, it sends a signal to the electrodes, which then apply electrical neurostimulation. The treatment is designed to prevent seizures before they occur.

Other IEEE student members involved in the project include Erik Biegert, Justin Pensock, Luke van der Spoel, and Randy Zhang (2016-2017 team) and Chris Harshaw, Victor Prieto, Michel Tsehaie, and Emily Meigs (2015-2016 team).

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