MRI-Based Skeletal Hand Movement Model

  • Georg StillfriedEmail author
  • Ulrich Hillenbrand
  • Marcus Settles
  • Patrick van der Smagt
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 95)


The kinematics of the human hand is optimal with respect to force distribution during pinch as well as power grasp, reducing the tissue strain when exerting forces through opposing fingers and optimising contact faces. Quantifying this optimality is of key importance when constructing biomimetic robotic hands, but understanding the exact human finger motion is also an important asset in, e.g. tracking finger movement during manipulation. The goal of the method presented here is to determine the precise orientations and positions of the axes of rotation of the finger joints by using suitable magnetic resonance imaging (MRI) images of a hand in various postures. The bones are segmented from the images, and their poses are estimated with respect to a reference posture. The axis orientations and positions are fitted numerically to match the measured bone motions. Eight joint types with varying degrees of freedom are investigated for each joint, and the joint type is selected by setting a limit on the rotational and translational mean discrepancy. The method results in hand models with differing accuracy and complexity, of which three examples, ranging from 22 to 33 DoF, are presented. The ranges of motion of the joints show some consensus and some disagreement with data from literature. One of the models is published as an implementation for the free OpenSim simulation environment. The mean discrepancies from a hand model built from MRI data are compared against a hand model built from optical motion capture data.


Human hand Robot hand Hand kinematics MR imaging 3D object localisation 




Metacarpal bone


Proximal phalanx


Medial phalanx


Distal phalanx



Carpometacarpal joint


Intermetacarpal joint


Metacarpophalangeal joint


Proximal interphalangeal joint


Distal interphalangeal joint


Thumb interphalangeal joint



Degree(s) of freedom


Leave-one-out cross-validation


Magnetic resonance imaging


(Optical) motion capture



The authors would like to thank Karolina Stonawska for the tedious work of segmenting the bones. This project was partly funded by the EU project The Hand Embodied (FP7-ICT-248587).


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Georg Stillfried
    • 1
    Email author
  • Ulrich Hillenbrand
    • 1
  • Marcus Settles
    • 2
  • Patrick van der Smagt
    • 3
  1. 1.Institute of Robotics and MechatronicsGerman Aerospace Center (DLR)WesslingGermany
  2. 2.Klinikum rechts der IsarUniversity hospital of TU MünchenMunichGermany
  3. 3.Faculty of InformaticsTechnische Universität MünchenMunichGermany

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