You are here

Combat Casualty Handoff Automated Trainer (CCHAT)

Award Information
Agency: Department of Defense
Branch: Defense Health Agency
Contract: W81XWH-18-C-0059
Agency Tracking Number: H17B-001-0018
Amount: $149,976.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: DHA17B-001
Solicitation Number: 2017.0
Solicitation Year: 2017
Award Year: 2018
Award Start Date (Proposal Award Date): 2017-12-18
Award End Date (Contract End Date): 2018-07-17
Small Business Information
3600 Green Court
Ann Arbor, MI 48105
United States
DUNS: 009485124
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Alyssa Tanaka
 (407) 249-0454
Business Contact
 Denise Nicholson
Phone: (407) 249-0454
Research Institution
 University of Central Florida
 Greg Welch
4000 Central Florida Boulevard
Orlando, FL 32816
United States

 (407) 796-2823
 Nonprofit College or University

Combat casualty handoffs are critical communication moments during which responsibility for the patient and important casualty information is transferred between providers. The nature of these handoffs requires specialized training, for which no standardized framework currently exists. The proposed effort aims to develop a capability, compatible with current DoD systems, that provides caregivers with the opportunity to master combat casualty handoff protocols, from the point of injury through the continuum of care. This solution, the Combat Casualty Handoff Automated Trainer (CCHAT), focuses on the verbal communication and proposes a speech recognition system that will automatically assess a trainees handoff performance in real-time.The proposed system will incorporate the speech protocol created by the DHA17B-002 performer. Using this protocol, trainees will perform a handoff in any simulated training environment. Their speech will be captured by the system and interpreted by the software. As the speech is interpreted, it is evaluated against the standardized speech protocol and populated in trainee and instructor user interfaces. These interfaces will provide in-situ performance feedback and AAR metrics. This effort will develop a TRL3 prototype system and demonstrate feasibility of speech recognition for handoff training.

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

US Flag An Official Website of the United States Government