SBIR-STTR Award

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to demonstrate the feasibility of an intelligent, wearable electroencephalogram (EEG) monitoring and analytics platform as a remote seizure detection system. Epilepsy is a neurological disorder affecting 50 million people of all ages globally. Over 3 million people in the U.S. are affected with 150,000 new cases diagnosed each year. However, identifying and characterizing the type of seizure can be costly. EEGs record the electrical activity of the brain and can be used for epilepsy diagnosis. Today, this test is administered in a hospital setting and the patient is monitored continuously for several days. This project will enable the end-to-end system development of a robust, lightweight, wireless EEG cap to transmit signals remotely to a server, which will generate reports for the physician to analyze a patient neurological data for treatment. The proposed technology is a long-term, lightweight ambulatory seizure monitoring system offering advantages, including 1) Patients no longer have to endure long hospital stays, 2) More seizure instances can be detected outside clinical settings, and 3) Costs of ongoing monitoring are lowered. This Small Business Innovation Research (SBIR) Phase I project will: (1) demonstrate that a proposed Analog Front End (AFE) is the most noise-power efficient in the EEG band (1-100 Hz) compared to benchmarks; (2) develop a system power budget to optimize signal processing in a low-power environment; and (3) perform signal integrity analysis of error sources (electronic noise, mains power interference, etc.) to optimize performance. The AFE is the foundation of a proposed portable electroencephalograph (EEG) device for neurological data acquisition for the clinical, academic, and research communities. This system will extend the current rise of digital health devices into the complex environment of neurological states, as well as advancing new neuro-analytic systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project provides next generation ambulatory seizure data acquisition. The advent of mobile health advances during the COVID-19 health crisis have enabled new innovations to be considered. This effort provides a framework for the next line of remote neurological data acquisition capabilities for the implementation of military helmet designs that detect battlefield traumatic brain injuries, football helmet designs that detect sports-related brain injuries, caps for first responder teams that detect trauma, at-home monitoring headsets for remote migraine assessment, etc. A complete analogue front end (AFE) will be developed in order to provide digitized electroencephalograph (EEG) signals to the downstream stages. The project will have a major impact in several areas, namely, wearable bio-devices, data fusion, and neurological data extraction and visualization of complex biological systems. This device can be utilized for first responders at the scene of neurological trauma such as emergency medical technicians, battle front medical areas, and sports related events.This Small Business Innovation Research Phase II project will provide a robust mobile device that can be worn in an at-home setting for remote neurological monitoring. The solution will remove noisy artifacts from the electroencephalograph signal in order to perform neurological diagnoses and provide neurological reporting to the neurologist as an aid to quantify the patient?s seizure instances. The analogue front end (AFE) provides the foundation for a portable electroencephalograph (EEG) device for neurological data acquisition for the clinical, academic, and research communities. The ambulatory seizure monitoring device will enable an end-to-end system for robust, lightweight, data transmission to a cloud service, which will generate reports for the physician to analyze a patient neurological data for treatment. This system will extend the current rise of health devices into the complex environment of neurological states, as well as the eventual development of neuro-analytics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.