A robust formulation for prediction of human running

Hyun Joon Chung, Yujiang Xiang, Anith Mathai, Salam Rahmatalla, Joo Hyun Kim, Timothy Marler, Steve Beck, Jingzhou Yang, Jasbir Arora, Karim Abdel-Malek, John Obusek

Research output: Chapter in Book/Report/Conference proceedingConference contribution


A method to simulate digital human running using an optimization-based approach is presented. The digital human is considered as a mechanical system that includes link lengths, mass moments of inertia, joint torques, and external forces. The problem is formulated as an optimization problem to determine the joint angle profiles. The kinematics analysis of the model is carried out using the Denavit-Hartenberg method. The B-spline approximation is used for discretization of the joint angle profiles, and the recursive formulation is used for the dynamic equilibrium analysis. The equations of motion thus obtained are treated as equality constraints in the optimization process. With this formulation, a method for the integration of constrained equations of motion is not required. This is a unique feature of the present formulation and has advantages for the numerical solution process. The formulation also offers considerable flexibility for simulating different running conditions quite routinely. The zero moment point (ZMP) constraint during the foot support phase is imposed in the optimization problem. The proposed approach works quite well, and several realistic simulations of human running are generated.

Original languageEnglish (US)
Title of host publicationDigital Human Modeling for Design and Engineering Conference and Exhibition
StatePublished - 2007
EventDigital Human Modeling for Design and Engineering Conference and Exhibition - Seattle, WA, United States
Duration: Jun 12 2007Jun 14 2007


OtherDigital Human Modeling for Design and Engineering Conference and Exhibition
Country/TerritoryUnited States
CitySeattle, WA

ASJC Scopus subject areas

  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Pollution
  • Industrial and Manufacturing Engineering


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