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Neck Load Simulation During Individual Warfighting Postures and Maneuvers

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-10-M-0445
Agency Tracking Number: N102-170-0009
Amount: $69,926.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N102-170
Solicitation Number: 2010.2
Timeline
Solicitation Year: 2010
Award Year: 2011
Award Start Date (Proposal Award Date): 2010-10-18
Award End Date (Contract End Date): N/A
Small Business Information
1634 Brandywine Drive
Charlottesville, VA -
United States
DUNS: 623531568
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Simeon Fitch
 Principal/Senior Software
 (434) 202-4332
 simeon.fitch@mseedsoft.com
Business Contact
 Simeon Fitch
Title: Principal/Senior Software
Phone: (434) 202-4332
Email: simeon.fitch@mseedsoft.com
Research Institution
 Stub
Abstract

The proposed project focuses on the development of a prototype application to estimate neck load of a dismounted Warfighter engaged in three common mission tasks (i.e. marching, running, and jumping), using an existing verified and validated physics-based computational neck model. In contrast to forward dynamics models (such as that described in (Ryan McCullough)), our physics-based cervical spine finite element model approach includes explicit representations of the head and full cervical column, including all vertebrae, intervertebral discs, ligaments, as well as active muscles, and can compute loads, stresses, and strains in each of these components as well as overall dynamic loading in the neck. Our model has been extensively verified and validated against a suite of quasi-static and dynamic experimental data and has been shown to be highly accurate. By employing a biomechanical component-based approach, where models for each tissue type are treated individually, we not only have a simulation that is more accurate and able to be better validated over a forward dynamics model, but that also results in higher-fidelity simulations able to predict very specific local injuries and overall (global) neck injuries with a high level of accuracy.

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

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