Real-time optimal reach-posture prediction in a new interactive virtual environment

Jingzhou Yang, R. Timothy Marler, Steven Beck, Karim Abdel-Malek, Joo Kim

Research output: Contribution to journalArticlepeer-review


Human posture prediction is a key factor for the design and evaluation of workspaces, in a virtual environment using virtual humans. This work presents a new interface and virtual environment for the direct human optimized posture prediction (D-HOPP) approach to predicting realistic reach postures of digital humans, where reach postures entail the use of the torso, arms, and neck. D-HOPP is based on the contention where depending on what type of task is being completed, and human posture is governed by different human performance measures. A human performance measure is a physics-based metric, such as energy or discomfort, and serves as an objective function in an optimization formulation. The problem is formulated as a single-objective optimization (SOO) problem with a single performance measure and as multi-objective-optimization (MOO) problem with multiple combined performance measures. We use joint displacement, change in potential energy, and musculoskeletal discomfort as performance measures. D-HOPP is equipped with an extensive yet intuitive user-interface, and the results are presented in an interactive virtual environment.

Original languageEnglish (US)
Pages (from-to)189-198
Number of pages10
JournalJournal of Computer Science and Technology
Issue number2
StatePublished - Mar 2006


  • Human modeling and simulation
  • MOO
  • Reach posture prediction
  • Virtual environment

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Science Applications
  • Computational Theory and Mathematics


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