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Physical Monitoring to Improve Warfighter Performance

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911NF-22-C-0029
Agency Tracking Number: A2-9168
Amount: $1,128,872.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: A20B-T008
Solicitation Number: 20.B
Timeline
Solicitation Year: 2020
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-06-01
Award End Date (Contract End Date): 2024-05-31
Small Business Information
7700 North Kendall Drive, Suite 300-A
miami, FL 33156-1111
United States
DUNS: 064660903
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Howard Wittels
 (305) 542-3142
 shwittels@gmail.com
Business Contact
 Harrison Wittels
Phone: (305) 799-8129
Email: hl@tigertech.solutions
Research Institution
 Mount Sinai Medical Center
 Robert Goldszer
 
4300 Alton Road
Miami Beach, FL 33140-0001
United States

 (305) 674-2121
 Nonprofit College or University
Abstract

In our Phase I study, Tiger Tech analyzed subjects before, during, and after cognitively challenging activities in order to identify biomarkers for the purpose of assessing and monitoring cognitive load.  Specifically, we took data on anesthesia providers administering healthcare over the course of an eight-hour work day.  By analyzing cardiac and vascular biometric signals, biomarkers were identified that indicated cognitive fatigue. These biomarkers can be utilized as part of a AI/ML warning system for identifying individuals who are no longer fit for duty as a result of cognitive exhaustion. Cognitive load biomarkers identified in Phase I will be the foundation for our research into the social dynamic of the team’s environment.  By leveraging our Phase I research and additional knowledge gained through continued research the Tiger Tech team will fill this gap by giving commanders the system needed to immediately assess the biophysiological and cognitive performance of each soldier and/or team. Tiger Tech is proposing a system that will distill only actionable information (e.g., cognitive load biomarkers) and will reduce data overload through on-chip processing without the use of cloud computing.

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

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