Ambulatory, Miniaturized, Automatic EEG Seizure Detector

Award Information
Agency: Department of Defense
Branch: Army
Contract: W81XWH-06-C-0016
Agency Tracking Number: A052-162-2339
Amount: $120,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2005
Solicitation Year: 2005
Solicitation Topic Code: A05-162
Solicitation Number: 2005.2
Small Business Information
NeuroWave Systems Inc.
2490 Lee Blvd, Suite 300, Cleveland Hts, OH, -
DUNS: 557510625
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Stephane Bibian
 Vice President, NeuroWave Division
 (216) 472-6337
 sbibian@neurowavesystems.com
Business Contact
 Robert Schmidt
Title: President
Phone: (216) 472-6338
Email: tzikov@neurowavesystems.com
Research Institution
N/A
Abstract
This program will develop an ambulatory, miniaturized, EEG acquisition/analysis device that will be capable of automatic and real-time detection of seizure activity including non-convulsive status epilepticus. The miniaturized EEG device, based on CleveMed's state-of-the art ambulatory EEG technology, measures 1.3" x .9" x .3" and weighs a mere .42 oz. Convenient and fast EEG acquisition is achieved by an elastic headband with attached physiological no-preparation "dry" electrodes. The EEG analysis and automatic seizure detection algorithms will be based on a novel combination of two high-resolution and computationally efficient seizure identification/prediction techniques that are currently being finalized in our company supported by separate grants from National Institute of Neurological Disorders and Stroke (NINDS). The ambulatory system will also utilize the EEG artifact removal technology that is being developed under another grant from NINDS. A computationally efficient implementation of these algorithms will be embedded in the PDA which will display the raw EEG as well as a continuously updated "Seizure Detection Index". The developed system will be evaluated at the Neurology department of the Cleveland Clinic with pre-recorded seizure data from epileptic patients (using a patient simulator) as well as with actual patients undergoing long-term term EEG monitoring.

* information listed above is at the time of submission.

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