Study on Movement Characteristics of Fingers During Hand Grabbing Process

  • Zhelin Li
  • Zunfu Wang
  • Yongyi Zhu
  • Lijun JiangEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 903)


Grabbing objects is the daily behavior of the human hand. The joint angle and correlation during the grasping process are the main movement characteristics of the finger. In this study, the OptiTrack motion capture system was used to collect the data. The analysis shows that: (1) In the three grasping modes, except thumb, the angle of the middle joint on the same finger changes the most, the proximal joint is the second, and the distal joint is the smallest. (2) The movement of the joint of the thumb has the lowest correlation with other four fingers. The conclusions of this study can be used on human-computer interaction research, rehabilitation analysis, prosthetic design and bionic robot development.


Finger Grasping Joint Correlation Angle 



This research is supported by the Fundamental Research Funds for the Central Universities 2017ZX013, and the Specialized Science Research Fund from Guangzhou Science Technology and Innovation Commission 201607010308.


  1. 1.
    Kamakura Moments: Finger kinematics. Phys. Med. Rehabil. 31, 122–125 (1991)Google Scholar
  2. 2.
    Santello, M., Flanders, M., Soechting, J.F.: Postural hand synergies for tool use. Neuroscience 18(23), 10105–10115 (1998)CrossRefGoogle Scholar
  3. 3.
    Eduardo, G.N., Faanha, F., Francisco, A.P., Davi, J., Barreto, C.M.: Modeling by correlation of the human hand for application in the robotic hand. In: 2017 IEEE 6th Global Conference on Consumer Electronics (GCCE 2017) (2017)Google Scholar
  4. 4.
    Liu, Y., Jiang, L., Yang, D., Liu, Y., Zhao, J., Liu, H.: Analysis on the joint independence of hand and wrist. In: AIM, pp. 31–37 (2016)Google Scholar
  5. 5.
    Qiaofei, Z.: Analysis of the characteristics of human hand movement and mechanical realization. Huazhong University of Science and Technology, Wuhan (2015)Google Scholar
  6. 6.
    Bullock, I.M., Zheng, J.Z., De La Rosa, S., Guertler, C., Dollar, A.M.: Grasp frequency and usage in daily household and machine shop tasks. IEEE Trans. Haptics 6(3), 296–308 (2013)CrossRefGoogle Scholar
  7. 7.
    Feix, T., Bullock, I.M., Dollar, A.M.: Analysis of human grasping behavior: object characteristics and grasp type. IEEE Trans. Haptics 7(4), 430–441 (2014)CrossRefGoogle Scholar
  8. 8.
    Miyata, N., Kouchi, M., Kurih, T., Mochimaru, M.: Modeling of human hand link structure from optical motion capture data. In: Proceedings of 2004 IEEElRSJ International Conference on Intelligent Robots and Systems, pp. 2129–2135 (2004)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Zhelin Li
    • 1
    • 2
  • Zunfu Wang
    • 1
  • Yongyi Zhu
    • 1
  • Lijun Jiang
    • 1
    • 2
    Email author
  1. 1.School of DesignSouth China University of TechnologyGuangzhouChina
  2. 2.Human-Computer Interaction Design Engineering Technology Research Center of GuangdongGuangzhouChina

Personalised recommendations