USA flag logo/image

An Official Website of the United States Government

A system for augmenting training by Monitoring, Extracting, and Decoding…

Award Information

Agency:
Department of Defense
Branch:
Defense Health Program
Award ID:
Program Year/Program:
2014 / SBIR
Agency Tracking Number:
H132-002-0021
Solicitation Year:
2013
Solicitation Topic Code:
DHP13-002
Solicitation Number:
2013.2
Small Business Information
Charles River Analytics Inc.
MA Cambridge, MA 02138-4555
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2014
Title: A system for augmenting training by Monitoring, Extracting, and Decoding Indicators of Cognitive Load (MEDIC)
Agency / Branch: DOD / DHP
Contract: W81XWH-14-C-0018
Award Amount: $150,000.00
 

Abstract:

Military medical personnel must act quickly and efficiently in any operational environment. Their success in saving lives depends on their ability to act effectively, both individually and as a team. Therefore, training must address individual skills and knowledge as well as interactions among team members. Currently, trainers must infer competence across these dimensions using only observation of trainee actiona challenging task. Automatically sensing indicators of cognitive load can provide information that augments performance observations, offering insight into how individuals and teams achieved that performance. Therefore, we propose to design and demonstrate a system for augmenting training by Monitoring, Extracting, and Decoding Indicators of Cognitive Load (MEDIC). MEDIC will use a multimodal suite of unobtrusive, field-ready neurophysiological and physiological sensors to disambiguate potential cognitive load indicators from other causes, such as physical exertion. MEDIC's sensor suite includes a user interface for trainers to enter observations and annotations for later review. MEDIC will use complex event processing to extract and fuse the best indicators of cognitive workload and team dynamics from the multiple, high-volume data streams originating from the sensor suite. MEDIC will also use novel probabilistic modeling techniques to help trainers interpret indicators during and after training.

Principal Investigator:

Bethany Bracken
Scientist
(617) 491-3474
bbracken@cra.com

Business Contact:

Mark Felix
Contracts Manager
(617) 491-3474
mfelix@cra.com
Small Business Information at Submission:

Charles River Analytics Inc.
625 Mount Auburn Street Cambridge, MA 02138-

EIN/Tax ID: 042803764
DUNS: N/A
Number of Employees:
Woman-Owned: Yes
Minority-Owned: No
HUBZone-Owned: No