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Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
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Human hand descriptions and gesture recognition for object manipulation.

Salvador Cobos1, Manuel Ferre, M Ángel Sánchez-Urán

  • 1Departamento de Automática, Ingeniería Electrónica e Informática Industrial, Universidad Politécnica de Madrid, C/José Gutiérrez Abascal, 2 28006 Madrid, Spain. cobosalvador@etsii.upm.es

Computer Methods in Biomechanics and Biomedical Engineering
|February 11, 2010
PubMed
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This study presents a realistic 24 degrees of freedom (DoF) human hand model for manipulation tasks. Simplified models with 6 and 9 DoF were developed, achieving high accuracy for gesture recognition.

Area of Science:

  • Robotics
  • Human-Computer Interaction
  • Biomechanics

Background:

  • Realistic human hand models are crucial for advanced manipulation tasks in robotics and virtual environments.
  • Existing models often lack the necessary fidelity to capture complex hand movements and constraints.

Purpose of the Study:

  • To develop a realistic kinematic model of the human hand with 24 degrees of freedom (DoF).
  • To create simplified hand models for efficient gesture recognition.
  • To establish criteria for selecting appropriate hand models for specific manipulation tasks.

Main Methods:

  • Defined a 24 DoF kinematic hand model based on morphological, physiological, and anatomical studies.
  • Incorporated intra- and inter-finger constraints to enhance realism.

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  • Developed a gesture recognition procedure using principal components analysis (PCA) and discriminant functions.
  • Created simplified 9 DoF and 6 DoF hand models.

    • Main Results:

    • The 24 DoF model satisfies realism requirements for simulation and movement.
    • Simplified models achieved high accuracy: ~5% error for the 9 DoF model and ~10% error for the 6 DoF model in gesture recognition.
    • Criteria for selecting hand model complexity based on task requirements were defined.

    Conclusions:

    • A realistic and adaptable human hand model with varying DoF can be achieved through anatomical study and constraint incorporation.
    • Simplified models offer a trade-off between complexity and accuracy for gesture recognition.
    • The defined criteria facilitate the selection of optimal hand models for diverse manipulation applications.