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Principled Design of an Augmented Reality Trainer for Medics

Award Information
Agency: Department of Defense
Branch: Defense Health Agency
Contract: W81XWH-17-C-0165
Agency Tracking Number: H17A-003-0035
Amount: $149,997.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: DHA17A-003
Solicitation Number: 2017.0
Solicitation Year: 2017
Award Year: 2017
Award Start Date (Proposal Award Date): 2017-08-01
Award End Date (Contract End Date): 2018-02-28
Small Business Information
3504 Lake Lynda Drive
Orlando, FL 32817
United States
DUNS: 075104708
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Dr. Anna Skinner
 Senior Research Associate III
 (407) 706-0977
Business Contact
 John Stanney
Phone: (407) 706-0977
Research Institution
 Eastern Virginia Medical School
 Bob Armstrong
825 Fairfax Ave
Norfolk, VA 23507
United States

 (757) 446-7121
 Nonprofit College or University

Design Interactive Inc. (DI) and Eastern Virginia Medical School (EVMS) propose to develop an Augmented reality Learning Environment for Refresher Training (ALERT) that provides realistic and relevant Tactical Combat Casualty Care (TC3) scenarios using AR technologies integrated with mannequins for pre-deployment training and humans for deployed training environments. ALERT will facilitate learning through scenario variations that strategically adapt training content complexity, instructional assistance, fidelity, and stressors based upon user level of expertise and training context. ALERT scenario design configurations will be guided by scientifically-grounded instructional strategies and design guidelines, which will be established via rigorous experimental testing and validation. ALERT will also facilitate learning via integrated modeling of multiple areas of the body and human anatomy rather than focusing on a single condition or area of the body, so that trainees experience learning via interconnected anatomy and develop foundational and generalizable skills. Additionally, ALERT will include embedded measures of performance and a capacity for adaptive training through intelligent coaching. The resulting solution will support both pre-deployment and deployable refresher training, and will also provide a testbed for empirically evaluating instructional approaches and AR technologies for medical training.

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

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