Individualized Fatigue Meter for Space Exploration

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: NNX10CA99C
Agency Tracking Number: 085176
Amount: $599,999.00
Phase: Phase II
Program: SBIR
Awards Year: 2010
Solicitation Year: N/A
Solicitation Topic Code: X11
Solicitation Number: N/A
Small Business Information
Pulsar Informatics, Inc.
3624 Market Street, Suite 5E, Philadelphia, PA, 19104
DUNS: 158273743
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Daniel Mollicone
 Principal Investigator
 (215) 520-2630
 Daniel@PulsarInformatics.com
Business Contact
 Daniel Mollicone
Title: Business Official
Phone: (215) 520-2630
Email: Daniel@PulsarInformatics.com
Research Institution
N/A
Abstract
To ensure mission success, astronauts must maintain a high level of performance even when work-rest schedules result in chronic sleep restriction and circadian misalignment, both of which contribute to fatigue and performance deficits unless effective countermeasures are used. We are proposing to build an Individualized Fatigue Meter that incorporates light inputs, sleep history, work schedule information, and brief performance tests (e.g. PVT SelfTest) to provide immediate individualized feedback about alertness. For the past 8 years, we have been actively developing many of the system components (funded by NASA, DOD, and NIH) that can be leveraged in this project. The result of this project will be a system prototype that can be evaluated using data already being collected in space flight analog expeditions (e.g., NEEMO, HMP) and on ISS. The critical need for an Individualized Fatigue Meter has been identified as a priority outlined in the Behavioral Health and Performance Integrated Research Plan GAP 1.1.1. During Phase 2 we will build a prototype Individualized Fatigue Meter by developing: (1) an interactive graphical console; (2) a model-independent computational architecture; (3) a hybrid biomathematical fatigue model; and (4) a data fusion algorithm that statistically combines multiple inputs (Phase 2 TRL of 5-6).

* information listed above is at the time of submission.

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