Skip to main content
SpringerLink
Log in

Virtual Environments for Hand Rehabilitation with Force Feedback

  • Conference paper
  • First Online:
Intelligent Robotics and Applications (ICIRA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9835))

Included in the following conference series:

  • 1685 Accesses

Abstract

Within recent years, an increasing number of researches that leverage virtual reality (VR) applications to improve motor rehabilitation have been conducted. These computer-based tools to various degrees help with motor rehabilitation for hand/arm impairment. Compared to the conventional therapy, people are more engaged and interested when they are being trained with the VR, leading to equal or higher improvements in terms of functional use of the hand/arm. In this paper, a VR-based platform for hand/arm rehabilitation is developed using delta3d, an open-source game and simulation engine of high-level interfaces to graphics and physics libraries. The platform provides not only visual information but also force feedback to users. Contrasted to previous similar researches, the contact force is directly extracted from the physics engine through virtual sensors. The effectiveness of virtual sensors is experimentally validated, and the relationship between joint angles and contact forces over time is presented. Finally, a training paradigm for hand impairment patients is proposed for future validation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Lambrecht, J.M., Pulliam, C.L., Kirsch, R.F.: Virtual reality environment for simulating tasks with a myoelectric prosthesis: an assessment and training tool. J. Prosthet. Orthot. 23, 89 (2011)

    Article  Google Scholar 

  2. Kuiken, T.A., Li, G., Lock, B.A., et al.: Targeted muscle reinnervation for real-time myoelectric control of multifunction artificial arms. Jama 301, 619–628 (2009)

    Article  Google Scholar 

  3. Hauschild, M., Davoodi, R., Loeb, G.E.: A virtual reality environment for designing and fitting neural prosthetic limbs. IEEE Trans. Neural Syst. Rehabil. Eng. 15, 9–15 (2007)

    Article  Google Scholar 

  4. Holden, M.K.: Virtual environments for motor rehabilitation: review. Cyberpsychol. Behav. 8, 187–211 (2005)

    Article  Google Scholar 

  5. Acosta, A.M., Dewald, H.A., Dewald, J.P.A.: Pilot study to test effectiveness of video game on reaching performance in stroke. J. Rehabil. Res. Dev. 48, 431 (2011)

    Article  Google Scholar 

  6. Lange, B., Chang, C.Y., Suma, E., et al.: Development and evaluation of low cost game-based balance rehabilitation tool using the Microsoft Kinect sensor. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, pp. 1831–1834. IEEE Press, Boston (2011)

    Google Scholar 

  7. Lange, B., Koenig, S., McConnell, E., et al.: Interactive game-based rehabilitation using the Microsoft Kinect. In: Virtual Reality Short Papers and Posters (VRW), pp. 171–172. IEEE (2012)

    Google Scholar 

  8. Popescu, V.G., Burdea, G.C., Bouzit, M., et al.: A virtual-reality-based telerehabilitation system with force feedback. IEEE Trans. Inf. Technol. Biomed. 4, 45–51 (2000)

    Article  Google Scholar 

  9. Jack, D., Boian, R., Merians, A.S., et al.: Virtual reality-enhanced stroke rehabilitation. IEEE Trans. Neural Syst. Rehabil. Eng. 9, 308–318 (2001)

    Article  Google Scholar 

  10. Sveistrup, H.: Motor rehabilitation using virtual reality. J. Neuroeng. Rehabil. 1, 1 (2004)

    Article  Google Scholar 

  11. delta3d. http://www.delta3d.org

  12. OpenSceneGraph Manual. http://www.openscenegraph.org/

  13. ODE Manual. http://ode-wiki.org/wiki/index.php?title=Manual

  14. Smith, R.: Constraints in rigid body dynamics. Game Program. Gems 4, 241–251 (2005)

    Google Scholar 

  15. Drumwright, E., Hsu, J., Koenig, N., Shell, D.: Extending open dynamics engine for robotics simulation. In: Ando, N., Balakirsky, S., Hemker, T., Reggiani, M., von Stryk, O. (eds.) SIMPAR 2010. LNCS, vol. 6472, pp. 38–50. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  16. Hsu, J.M., Peters, S.C.: Extending open dynamics engine for the DARPA virtual robotics challenge. In: Brugali, D., Broenink, J.F., Kroeger, T., MacDonald, B.A. (eds.) SIMPAR 2014. LNCS, vol. 8810, pp. 37–48. Springer, Heidelberg (2014)

    Google Scholar 

  17. 5DT Data Glove 14 Ultra Manual. http://www.5dt.com/products/pdataglove5u.html

Download references

Acknowledgments

This work is supported by the National Basic Research Program (973 Program) of China (Grant No. 2011CB013305), the National Natural Science Foundation of China (Grant No. 51375296).

Author information

Authors and Affiliations

  1. State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, 200240, China

    Wei Lv, Xinjun Sheng, Lei Hua & Xiangyang Zhu

Authors
  1. Wei Lv
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xinjun Sheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lei Hua
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiangyang Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xinjun Sheng .

Editor information

Editors and Affiliations

  1. Tokyo Metropolitan University , Tokyo, Japan

    Naoyuki Kubota

  2. Kyushu University , Fukuoka, Japan

    Kazuo Kiguchi

  3. University of Portsmouth , Portsmouth, United Kingdom

    Honghai Liu

  4. Tokyo Metropolitan University , Tokyo, Japan

    Takenori Obo

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Lv, W., Sheng, X., Hua, L., Zhu, X. (2016). Virtual Environments for Hand Rehabilitation with Force Feedback. In: Kubota, N., Kiguchi, K., Liu, H., Obo, T. (eds) Intelligent Robotics and Applications. ICIRA 2016. Lecture Notes in Computer Science(), vol 9835. Springer, Cham. https://doi.org/10.1007/978-3-319-43518-3_44

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-43518-3_44

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43517-6

  • Online ISBN: 978-3-319-43518-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation