Sensitive and Diagnostic Mental Workload Classifier

Award Information
Agency: Department of Defense
Branch: Army
Contract: W91CRB-13-C-0007
Agency Tracking Number: A122-087-0359
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2013
Solicitation Year: 2012
Solicitation Topic Code: A12-087
Solicitation Number: 2012.2
Small Business Information
2237 Faraday Ave, Suite 100, Carlsbad, CA, -
DUNS: 969842715
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Chris Berka
 (760) 720-0099
Business Contact
 Sandy Crow
Title: VP, Gov't Contracts
Phone: (760) 720-0099
Research Institution
We propose to develop a sensitive and selective workload classifier, called PHYSIOPRINT (Physiology and Performance Research Integration Tool), that will ultimately operate in real time on multiple physiological signals (EEG, EKG, EOG, EMG) acquired and processed by our wearable and wireless X24 system. The raw signals will be converted into input variables for the classifier using a suite of proprietary real-time algorithms that include noise reduction, spectral decomposition and topographic mapping of the EEG signals, extraction of event-related potentials, detection of eye blinks and fixations, calculation of heart rate and heart rate variability, detection of EMG bursts and tonic activity, calculation of respiratory rate and detection of the head/body position and movements. PHYSIOPRINT will be designed around the IMPRINT model of mental workload and will discriminate between seven workload types (visual, auditory, cognitive, speech, tactile, fine and gross motor). PHYSIOPRINT will also provide a measure of overall workload construed to account for potential conflicts between different types of workload. Phase I research, which will include analysis of a large database of physiological data acquired during military-relevant tasks and a pilot study in a driving simulator, will define the PHYSIOPRINT design concept and development approach for Phase II.

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

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