SBIR/STTR Research Award

Multi-Modal Neurodiagnostic Tool for Exploration Missions

Award identifier 13102f73d8f440dd046d894ad5cb6159f4c843ab6139e03c0c37d706c046195aAwarding agency National Aeronautics and Space Administration

Award amount

$749,877

Program and phase

SBIR · Phase II

Award year

2013

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Award details

Awarding agency
National Aeronautics and Space Administration
Branch
Not reported
Recipient company
Linea Research Corporation
Proposal award date
2012-12-11
Contract end date
2014-12-10
UEI
Not reported
Solicitation number
Not reported
Topic code
X13.01

Research abstract

NASA has a critical requirement for a neurodiagnostic tool that can be used to monitor the behavioral health of the crew during long duration exploration missions. The device should unobtrusively monitor and classify neurophysiological markers associated with decrements in behavioral state and cognition. The neurodiagnostic monitor should be lightweight and compact and should require minimal time or effort for the crew to use. The device should be unobtrusive enough to allow mission operations to be performed during monitoring. In Phase 1 of the program, we were able to successfully monitor cortical activity using multi-parameter sensor modules. In addition to electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) signals that provided the electrophysiological and cortical oxygenation information, we were able to obtain photoplethysmography (PPG) and electrooculography (EOG) signals to compute the heart rate and frequency of eye movement. In Phase 1 we also demonstrated the functionality of an algorithm that automatically classifies the varying degrees of cognitive loading based on the measured physiological parameters. In the proposed Phase 2 program, we will develop a flight-capable neurodiagnostic device that can be unobtrusively worn on the head. Based on the neuro and non-neurophysiological parameters obtained from the multi-modality sensors, we will detect and classify neurophysiological markers associated with decrements in behavioral state and cognition. We will develop an automated algorithm that can recognize and identify key decrements in behavioral state.

Technology keywords

Not reported

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Agency intelligence

National Aeronautics and Space Administration

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