Overuse Injury Assessment Model

Abstract

The aim of the present research is to equip our military leaders with knowledge and software tools which better assist them in the design of boot camp training regimens. More specifically, our research enhances of the state-of-the-art in bone overuse injury prediction. A significant part of our effort is geared towards the prediction and analysis of skeletal strain fields which result during a specific pattern of locomotion and for a given skeletal morphology. Once the intrinsic loads on the skeleton are known for various activities, it is possible to make educated inferences on how different training programs affect skeletal fatigue life, or in other words, the injury rate. First we researched and evaluated different approaches taken by others who have attempted to predict bone overuse injury rates before us. We then embarked on a multifaceted approach which utilizes biomechanics, inverse dynamics, static optimization, structural analysis, and statistical regression to determine skeletal fatigue, loads during locomotion. The present deliverable is a model which accepts experimental video and force plate data gathered from normal gait as inputs and then determines the strain fields which arise due to the observed locomotion in a realistic simulated femur.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2004
Accession Number
ADA423332

Entities

People

  • James H. Stuhmiller

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Basic Training
  • Bioengineering
  • Biomechanics
  • Bone And Bones
  • Bone Diseases
  • Bone Fractures
  • Computer Programs
  • Joints (Anatomy)
  • Literature Surveys
  • Mechanical Properties
  • Mechanics
  • Orthopedic Surgical Procedures
  • Orthopedics
  • Predictive Modeling
  • Radiography
  • Structural Analysis
  • X-Ray Computed Tomography

Readers

  • Computational Modeling and Simulation
  • Robotics and Automation.
  • Trauma Surgery or Emergency Medicine.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference