Lifting Posture Analysis in Material Handling Using Virtual Humans

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.Copyright © 2005 by ASME

[1]  Alexander Rm,et al.  A minimum energy cost hypothesis for human arm trajectories. , 1997 .

[2]  A. Hill.  The heat of shortening and the dynamic constants of muscle , 1938 .

[3]  Bruno Siciliano,et al.  Adaptive compliant control of robot manipulators , 1996 .

[4]  Maury A. Nussbaum,et al.  Effects of training in modifying working methods during common patient-handling activities , 2001 .

[5]  F.E. Zajac,et al.  Paraplegic standing controlled by functional neuromuscular stimulation. I. Computer model and control-system design , 1989, IEEE Transactions on Biomedical Engineering.

[6]  M G Pandy,et al.  Static and dynamic optimization solutions for gait are practically equivalent. , 2001, Journal of biomechanics.

[7]  Joo Hyun Kim,et al.  Layout Design using an Optimization-Based Human Energy Consumption Formulation , 2004 .

[8]  Jingzhou Yang,et al.  Multi-objective Optimization for Upper Body Posture Prediction , 2004 .

[9]  Michael A. Saunders,et al.  SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization , 2002, SIAM J. Optim..

[10]  Bruno Siciliano,et al.  Modeling and Control of Robot Manipulators , 1995 .

[11]  Min K. Chung,et al.  Evaluation of lifting tasks frequently performed during fire brick manufacturing processes using NIOSH lifting equations , 2000 .

[12]  S. Gallagher,et al.  Effects of posture on dynamic back loading during a cable lifting task , 2002, Ergonomics.

[13]  Kazunori Hase,et al.  Development of Three-Diemnsional Whole-Body Musculoskeletal Model for Various Motion Analyses , 1997 .

[14]  Don B. Chaffin,et al.  Development of Computerized Human Static Strength Simulation Model for Job Design , 1997 .

[15]  M. Pandy,et al.  A phenomenological model for estimating metabolic energy consumption in muscle contraction. , 2004, Journal of biomechanics.

[16]  Philip E. Martin,et al.  A Model of Human Muscle Energy Expenditure , 2003, Computer methods in biomechanics and biomedical engineering.