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Protective Mask Sizing App

Award Information
Agency: Department of Defense
Branch: Office for Chemical and Biological Defense
Contract: W911SR-16-C-0024
Agency Tracking Number: C161-005-0033
Amount: $149,988.35
Phase: Phase I
Program: SBIR
Solicitation Topic Code: CBD161-005
Solicitation Number: 2016.1
Timeline
Solicitation Year: 2016
Award Year: 2016
Award Start Date (Proposal Award Date): 2016-07-18
Award End Date (Contract End Date): 2017-01-18
Small Business Information
701 McMillian Way NW
Huntsville, AL 35806
United States
DUNS: 185169620
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: Yes
Principal Investigator
 Dr. Kay Sun
 (256) 726-4800
 proposals-contracts@cfdrc.com
Business Contact
 Mrs. Deb Phipps
Phone: (256) 726-4884
Email: deb.phipps@cfdrc.com
Research Institution
N/A
Abstract

Typical procedures for respirator masks sizing and protective fit test are time-consuming and user intensive, requiring taking anthropometric measurements of the wearer, sampling the wearers breathing zone and the use of specialized tools and equipment. The proposed software app aims to quickly, accurately and automatically perform respirator mask sizing and predict protective fit using only 2D images captured on smartphone cameras, thereby replacing the lengthy physical testing procedures and can even be performed in the field when needed. From the 2D images captured, personalized 3D face and head surfaces are generated through shape reconstruction in real-time. Common facial and head anthropometric measurements (face and menton-sellion lengths, face and lips breadth, head and neck circumferences, etc.) are automatically extracted from the mesh and are then used to predict respirator mask size according to National Institute for Occupational Safety and Health (NIOSH), Los Alamos National Laboratory (LANL) and custom respirator test fit panels. Further enhancements in Phase II will involve the development of individualized respiration models to simulate the movement of air and particulates through the mask and into the lungs in order to predict quantitative fit factor. Validation studies will also be performed to ensure the accuracy of the app predictions.

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

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