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Human Grasp Prediction and Analysis

In: Safety and Risk Modeling and Its Applications

Author

Listed:
  • Tim Marler

    (University of Iowa)

  • Ross Johnson

    (University of Iowa)

  • Faisal Goussous

    (University of Iowa)

  • Chris Murphy

    (University of Iowa)

  • Steve Beck

    (University of Iowa)

  • Karim Abdel-Malek

    (University of Iowa)

Abstract

Given that one of the critical motivations for using virtual humans is to simulate the interaction between humans and products, and given that using one’s hands are a primary means for interaction, then simulating human hands is arguably one of the most important elements of digital human modeling (DHM). Consequently, there is much research and development in this area, ranging from basic model development to detailed simulations of specific joints and tendons. However, when considering hand simulation and analysis within the context of a complete high-level DHM, the culmination of hand-related capabilities is grasping prediction. Thus, the focus of this chapter is on postural simulation and analysis capabilities of the overall hand as a component of a complete high-level DHM, with an eye toward grasping prediction. Within this context, the fundamental necessary elements one must consider when modeling the hand are highlighted. The intent is to provide general guidelines for creating computational models of hands and to present novel modeling and simulation techniques.

Suggested Citation

  • Tim Marler & Ross Johnson & Faisal Goussous & Chris Murphy & Steve Beck & Karim Abdel-Malek, 2011. "Human Grasp Prediction and Analysis," Springer Series in Reliability Engineering, in: Hoang Pham (ed.), Safety and Risk Modeling and Its Applications, pages 397-424, Springer.
  • Handle: RePEc:spr:ssrchp:978-0-85729-470-8_14
    DOI: 10.1007/978-0-85729-470-8_14
    as

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