Skip to main content

Neural Control of a Virtual Prosthesis

  • Conference paper
  • First Online:
Book cover ICANN 98 (ICANN 1998)

Part of the book series: Perspectives in Neural Computing ((PERSPECT.NEURAL))

Included in the following conference series:

Abstract

The abilities of the currently existing hand prostheses are typically limited to opening or closing the hand. This limits the usefulness of the prosthesis considerably compared to the many degrees of freedom in an intact hand. In order to develop more advanced hand prostheses two main problems have to be solved. The first is to develop more advanced mechanical solutions that allows for more degrees of freedom. The second, that we address below, is to devise a way of controlling the additional dexterity of such a prosthesis. Before the second problem is solved, the development of more advanced prostheses will be severely hindered.

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

Access this chapter

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 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Eriksson L. Sebelius F. Pattern recognition of nerve signals using artificial neural networks. M.Sc. thesis, Department of Solid State Physics, Lund University, 1996

    Google Scholar 

  2. Montelius L, Sebelius F, Eriksson L, Holmberg H, Schouenbourg J, Danielsen N, Wallman L, Laurell T, Balkenius C. (1996). Pattern recognition of nerve signals using an artificial neural network. Proceedings of the 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1996

    Google Scholar 

  3. Deutch, S. and Deutch, A. Understanding the Nervous System. IEEE Press, New York, 1992

    MATH  Google Scholar 

  4. Kohonen, T. Self-organization and associative memory. Springer-Verlag, Berlin, 1984

    MATH  Google Scholar 

  5. DeSieno, D. Adding a conscience to competitive learning. IEEE International Conference on Neural Networks, IEEE Press, New York, 1988, vol. 1, pp 117–124

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1998 Springer-Verlag London

About this paper

Cite this paper

Eriksson, L., Sebelius, F., Balkenius, C. (1998). Neural Control of a Virtual Prosthesis. In: Niklasson, L., Bodén, M., Ziemke, T. (eds) ICANN 98. ICANN 1998. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-1599-1_141

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-1599-1_141

  • Published:

  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-76263-8

  • Online ISBN: 978-1-4471-1599-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics