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Bioelectronic Fusion Sensor System

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-14-P-1206
Agency Tracking Number: N14A-019-0155
Amount: $79,794.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N14A-T019
Solicitation Number: 2014.
Solicitation Year: 2014
Award Year: 2014
Award Start Date (Proposal Award Date): 2014-08-04
Award End Date (Contract End Date): 2015-06-04
Small Business Information
850 Energy Drive Suite 307
Idaho Falls, ID -
United States
DUNS: 089822014
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Jennifer Haggerty
 (716) 830-4515
Business Contact
 Sonia Vohnout
Title: Director of Government Pr
Phone: (520) 704-7067
Research Institution
 University of Buffalo
 Albert Titus
332D Bonner Hall 332D Bonner Hall
Buffalo, NY 14250-
United States

 (716) 645-1019
 Nonprofit college or university

To address the Navy"s need for a common, scalable, platform for multi-modal 1pA level current sensing for Electrocardiogram (ECG), Electroencephalogram (EEG), and Electrodermal Response (EDR) to be fielded as a miniature wearable device with non-contact electrodes, Sentient and the State University of New York (SUNY) propose to develop the Bioelectronic Fusion Sensor System (BioFuSenS) that will assess a subject"s stress, fatigue and resilience. BioFuSenS will be modular, real-time, low cost, low bandwidth, open standards-based, including autonomous prediction, health monitoring and management. Innovation is based on an ultra-sensitive, multi-channel, compact low power integrated circuit (IC), combined with mechanical sensing, a Bayesian-based data-model fusion algorithm, and ground truth data model. BioFuSenS is supported by"Predict-Acquire-Confirm-Control"process for monitoring center or remote operation. Energy harvesting for full power management and immunity to motion artifacts and muscle noises through robust and accurate data-model fusion is enabled, addressing the requirements of the Navy. In Phase I, we demonstrate feasibility through transistor-level IC simulations, thorough nonlinear systems analysis, and data-model fusion and noise handling simulations for ECG sensing. In Phase II, we will develop/validate a prototype, demonstrate multi-modal, model-based detection with noise filtering, and optimize the design to meet size, weight, power, and cost (SWAP-C) requirements.

* Information listed above is at the time of submission. *

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