SBIR-STTR Award

Open Call for Robotics, 3D Printing, Autonomous Systems, and Other Immersive Training Solutions with Defense-Related Dual-Purpose Technologies/Solutions with a Clear Air Force Stakeholder Need
Award last edited on: 3/24/2023

Sponsored Program
SBIR
Awarding Agency
DOD : AF
Total Award Amount
$2,510,316
Award Phase
2
Solicitation Topic Code
AF191-004
Principal Investigator
Patricia Herrmann

Company Information

Senseye Inc

801 Congress Avenue Suite 200
Austin, TX 78704
   (847) 707-2668
   hello@senseye.co
   www.senseye.co
Location: Single
Congr. District: 37
County: Travis

Phase I

Contract Number: FA3002-19-P-A109
Start Date: 3/6/2019    Completed: 3/6/2020
Phase I year
2019
Phase I Amount
$60,316
Senseye, Inc is small, technology-driven business located in Austin, TX. Senseye believes that the eyes provide a means for our brains to perceive the world around us. The eyes also provide a window into the inner processes of the brain. Our research shows the human iris muscles are controlled by deep structures in the brain reflecting autonomic arousal and cognitive processing. Building upon prior research, Senseye has advanced lab results showing that mental states and emotions can be accurately observed from analyzing complex dynamic properties of the human eye. Ultimately, through capturing and combining multiple sources of biometric data and using advanced analytics not previously available, Senseye is working towards developing and creating direct links between the human brain and computers via the eye (Human Computer Symbiosis). Senseye has developed an Emotional Intelligence Engine platform (EIE) as the foundation used for emotional response recognition. Using the EIE and a commercial-off-the-shelf camera, movements of ocular muscle fibers are measured in a manner that permits the monitoring of brain activity.

Phase II

Contract Number: FA3002-19-P-A181
Start Date: 7/14/2019    Completed: 10/31/2020
Phase II year
2019
Phase II Amount
$2,450,000
The Senseye ORM System is a stand-off operational risk management platform that ensures an individual is fit for duty within that moment in time. The platform can detect through a short ocular task if a person has any drugs or alcohol in their system, is fatigued, or is under psychological distress. The platform will provide a red or green light to the end user that will indicate to them whether they are fit for duty or not at the time of assessment, including the reason why a red light was flagged. Also, the platform will allow supervisors to login and view past test results by end users. The system is currently being beta tested for the private sector to assess operational risk in the marine shipping and oil & gas industries.