Development and Validation of Human Digital Twin to Predict Injury Risks under Military Relevant Conditions
Abstract
Military personnel can suffer from a wide range of injuries ranging from severe singular impacts during active warfare and accidents to repetitive accumulation of acute injuries during routine operations. To minimize the risk of injury and increase military readiness, there is a critical need to design effective protective equipment and training protocols, which in turn require understanding the mechanical loads on military personnel in different operational environments and the corresponding risk of injury. Since conducting physical experiments to gain this insight can be expensive and time consuming, computational models are a powerful tool for providing crucial insight into the risk of injury for a wide range of operational environments. There has been a focused effort towards developing bio-fidelic human digital twins (HDT) to simulate accurate loading on military personnel. The PANTHER and the I-PREDICT programs, supported through the Office of Naval Research (ONR), have been developing state-of-the-art human brain and human body computational models, respectively. In this proposal, we will combine these models to provide an integrated tool for injury risk prediction under military-relevant loading conditions. The integrated model will be applied to perform a full body injury risk assessment under blunt impact loading conditions. The model performance will be demonstrated through two military-relevant case studies: (1) fuselage drop and (2) fast boat ride. These simulations will provide critical insight into safe exposure limits with the goal of reducing the risk of injury and maximizing military readiness.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 08, 2024
- Source ID
- N000142412415
Entities
People
- Rika Wright Carlsen
Organizations
- Office of Naval Research
- Robert Morris University
- United States Navy