Lifting Posture Analysis in Material Handling Using Virtual Humans

Abstract

Adopting appropriate postures during manual material-handling tasks is the key to reducing human joint injuries. Although much experimentation has been conducted in an effort to model lifting, such an approach is not general enough to consider all potential scenarios in material handling. Thus, in this paper an optimization-based motion prediction method is used to simulate realistic lifting postures and predict joint torques to evaluate the risk level of injury. A kinematically realistic digital human model has been developed such that the complicated musculoskeletal human structure is modeled as a combination of serial chains using the generalized coordinates. Lagrange?s equations of motion and metabolic energy rate are derived for the digital human. The proposed method has been implemented to predict and evaluate the lifting postures based on the metabolic rate and joint torques. Our results show that different amount of external loads and tasks lead to different human postures and joint torque distribution, thus different risk level of injury.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2005
Accession Number
ADA591894

Entities

People

  • Jingzhou Yang
  • Joo H. Kim
  • Karim Abdel-malek
  • Kyle Nebel
  • Timothy Marler

Organizations

  • University of Iowa

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Back Injuries
  • Biomechanical Phenomena
  • Computer Programs
  • Computer-Aided Design
  • Computers
  • Coordinate Systems
  • Elastic Properties
  • Equations
  • Equations Of Motion
  • Heat Energy
  • Motor Skills
  • Muscles
  • Musculoskeletal System
  • Physical Properties
  • Simulations
  • Skeletal Muscle
  • Spinal Column

Readers

  • Computational Modeling and Simulation
  • Logistics and Supply Chain Management.
  • Robotics and Automation.