Grant Funds Medical Device Development to Prevent Epileptic Seizures

A professor at the University of Houston has received a $3.7 million BRAIN initiative grant from the National Institute of Neurological Disorders and Stroke to further his research and medical device development for epileptic seizure prevention.

Nuri Firat Ince, associate professor of biomedical engineering, decreased the time it takes to identify the seizure onset zone—the part of the brain that causes an epileptic seizure—by detecting high frequency oscillations that reveal their zone location with repetitive waveform patterns.

Ince intends to translate the high frequency oscillations into seizure control applications in order to identify and prevent seizures in individuals before they even begin. A portion of the grant will fund his research about whether an implantable brain device can detect the high frequency oscillations.

“If this can be achieved, then HFOs can be strategically translated as a neurobiomarker into closed-loop seizure control applications,” Ince said in the press release.

“We hypothesize that pathologic stereotyped HFOs can be captured with the implantable Brain Interchange (BIC) system and spatial topography of these events can be utilized by the implantable system to deliver targeted electrical stimulation to achieve seizure control.”

The project’s neurotech partner, Cortec GMBH of Freiburg, Germany, will supply the Brain Interchange system. Once Ince and researchers finalize the implantable device, researchers will observe the children and adult epilepsy patients who receive the device at Houston’s Baylor College of Medicine, the project’s clinical partner.

If the research on the Brain Interchange implant in acute settings yields successful outcomes, then there will be a clinical trial in a chronic ambulatory setting.

Unlike responsive neurostimulation devices, Ince’s brain implant device does not have to wait for a seizure to start before it can notify the patient about potential onset, according to Ince.

Leading up to his development of the Brain Interchange system, Ince differentiated between waveforms that appeared in a seizure onset zone and waveforms in non-epileptic sites like motor and language cortices.

“Specifically, in our preliminary studies, we observed that the SOZ repeatedly generates sets of stereotypical HFO waveforms whereas the events generated from other brain areas were polymorphic,” Ince clarified.

“This pattern served as a robust neurobiomarker to isolate the SOZ from other brain areas. While promising preliminary results are in place, the functional utility of stereotyped HFOs in a closed-loop seizure control system remains unknown.”

Experts have employed different devices and mHealth technologies to attempt to detect epileptic seizures.

In 2018, the US Food and Drug Administration (FDA) approved an mHealth wearable that used machine learning to measure electrodermal activity and detect a seizure. The wearable would then send text and email alerts to care team members for assistance. The FDA authorized the wearable for children as young as 6 in January 2019.

A past Mayo Clinic study also found that an mHealth app saw success in diagnosing epilepsy. After patients experienced a seizure, doctors entered the information into the app and it was able to discern whether the seizure was an epilepsy syndrome or a separate diagnosis.