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Optimizing Human-Automation Team Workload through a Non-Invasive Detection System

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: 140D63-18-C-0039
Agency Tracking Number: D2-2056
Amount: $1,494,579.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: ST16C-003
Solicitation Number: 16.C
Timeline
Solicitation Year: 2016
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-07-02
Award End Date (Contract End Date): 2022-03-01
Small Business Information
1650 South Amphlett Blvd. Suite 300
San Mateo, CA 94402
United States
DUNS: 608176715
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Aaron Novstrup
 Principal Investigator
 (206) 430-7736
 anovstrup@stottlerhenke.com
Business Contact
 Nate Henke
Phone: (650) 931-2700
Email: nhenke@stottlerhenke.com
Research Institution
 Massachusetts General Hospital
 Susan Buchan Susan Buchan
 
399 Revolution Drive
Somerville, MA 02145
United States

 (857) 282-1718
 Domestic nonprofit research organization
Abstract

We propose to investigate, in collaboration with MGH Voice Center and Altec, Inc., application of surface electromyography (sEMG) to assessing cognitive workload, strain, and overload. Specifically, sEMG sensors placed on the face and neck will detect emotional/motor responses to workload strain. The proposed effort will build on the substantial sEMG experience of our partner, MGH (including research on vocal/subvocal speech recognition) as well as Altec’s foundation of unobtrusive, wireless sEMG sensing/signal processing equipment and our state-of-the-art technology for real-time human state assessment—ultimately resulting in a robust, reliable, highly sensitive model for estimating workload strain and detecting and predicting cognitive overload in real time. The system, called Empathy, will employ a complement of cost-effective, unobtrusive psychophysiological sensors designed/chosen to minimize artificial constraints on operator behavior, as well as utilizing additional sources of evidence reflecting an operator’s internal state (e.g., attention dynamics, physical performance, status of the automation involved). Phase II will build on the analytical/theoretical progress of Phase I by empirically validating the utility of sEMG for this application. A complete, integrated prototype will be developed, tested in a laboratory setting under operationally relevant conditions, and delivered to DARPA/AFRL for further testing/evaluation by the end of the Phase II Option.

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

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