# Optimizing Pharmacotherapy with Noninvasive Wearable Sensors and Subscalp EEG

> **NIH NIH UG3** · MAYO CLINIC ROCHESTER · 2022 · $604,937

## Abstract

Project Summary
The apparently random nature of seizures is one of the most significant factors affecting quality of life for patients
with epilepsy. Accurate seizure forecasting could be transformative for patients with epilepsy, allowing patients
to modify activities to avoid risk, take fast-acting medications to stop seizures before they develop, and provide
a sense of empowerment over their disease. Successful seizure prediction has now been established using
ambulatory intracranial EEG devices. Unfortunately, no such device is currently available to patients, as no
commercial vendor has been successful to date at obtaining approval for clinical use of such a device.
Furthermore, invasive intracranial implants may not be appropriate for or acceptable to many patients given the
associated risk of infection and hemorrhage. Subscalp EEG recording has recently emerged as a viable means
for long-term monitoring of patients with epilepsy. A device is commercially available in the EU, but does not
yet have FDA clearance in the US. Recently published studies show the device to be reliable and robust, and
recordings longer than 6 months have been reported. In addition cycles of seizure risk have been identified in
wearable device physiological signals, and these long-term cycles may be capable of contributing to the
accuracy of seizure forecasts. This project will develop the ability to prospectively forecast seizures from
simultaneous subscalp EEG and wrist-worn wearable signals, and will assess the safety and feasibility of
administering a fast-acting supplemental medication with seizure forecasts to prevent seizures.

## Key facts

- **NIH application ID:** 10286466
- **Project number:** 1UG3NS123066-01
- **Recipient organization:** MAYO CLINIC ROCHESTER
- **Principal Investigator:** Benjamin H Brinkmann
- **Activity code:** UG3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $604,937
- **Award type:** 1
- **Project period:** 2022-02-04 → 2025-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10286466

## Citation

> US National Institutes of Health, RePORTER application 10286466, Optimizing Pharmacotherapy with Noninvasive Wearable Sensors and Subscalp EEG (1UG3NS123066-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10286466. Licensed CC0.

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