Skip to main content

A Study of the Electric Wheelchair Hands-Free Safety Control System Using the Surface-Electromygram of Facial Muscles

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6425))

Abstract

The goal of Human-Computer Interface (or called Human-Robot interface) research is to provide humans with a new communication channel that allows translating people’s intention states via a computer into performing specific actions. This paper presents a novel hands-free control system for controlling the electric wheelchair, which is based on Bio-signals as surface electromyogram signals. The Bioelectric signals are picked up from facial muscles then the Bio-signals are passed through an amplifier and a high pass filter. Motion control commands (Forward, Left, Right, Forward to the Right, Forward to the left and Stop) are classified by simple rule. These commands are used for controlling the electric wheelchair.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Tomohiro, K., Tadashi, M., Tohru, K., Tsugutake, S.: Practical Usage of Surface Electromyogram, Biomechanism Library (2006)

    Google Scholar 

  2. Assareh, A., Konjkav, S., Fallah, A., Firoozabadi, S.M.P.: A New Approach for Navigating Automatic Wheelchairs using EMG signals Feature Extraction and Classification with an Adaptive Controller. In: Proc. The 12th International Conference on Biomedical Engineering, Singapore (December 2005)

    Google Scholar 

  3. Firoozabadi, S.M.P., Asghari Oskoei, M., Hu, H.: A Human-Computer Interface based on Forehead Multi-channel Bio-signals to control a virtual wheelchair. In: Proceedings of the 14th Iranian Conference on Biomedical Engineering (ICBME), pp. 272–277. Shahed University, Iran (February 2008)

    Google Scholar 

  4. Tamura, H., Okumura, D., Tanno, K.: A Study of Motion Recognition without FFT from Surface-EMG. The Journal of IEICE D J90-D(9), 2652–2655 (2007)

    Google Scholar 

  5. Okumura, D., Tamura, H., Tanno, K.: Proposal of the Motion Recognition system corresponding Sarface-EMG changes. In: Proceedings of Forum on Information Technology, FIT 2007, pp. G-022 (2007) (Japanese)

    Google Scholar 

  6. Tamure, H., Gotoh, T., Okumura, D., Tanaka, H., Tanno, K.: A Study on the s-EMG Pattern Recognition using Neural Network. International Journal of Innovative Computing, Information and Control 5(12), 4877–4884 (2009)

    Google Scholar 

  7. Manabe, T., Tamura, H., Tanno, K.: The Control Experiments of the Electric Wheelchair using s-EMG of Facial Muscles. In: Proceedings of Forum on Information Technology (FIT 2009), (CD-ROM), pp. K-008 (2009) (Japanese)

    Google Scholar 

  8. Jia, P., Hu, H.H., Lu, T., Yuan, K.: Head gesture recognition for hands-free control of an intelligent wheelchair. Industrial Robot: An International Journal 34(1), 60–68 (2007)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Tamura, H., Manabe, T., Goto, T., Yamashita, Y., Tanno, K. (2010). A Study of the Electric Wheelchair Hands-Free Safety Control System Using the Surface-Electromygram of Facial Muscles. In: Liu, H., Ding, H., Xiong, Z., Zhu, X. (eds) Intelligent Robotics and Applications. ICIRA 2010. Lecture Notes in Computer Science(), vol 6425. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16587-0_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-16587-0_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16586-3

  • Online ISBN: 978-3-642-16587-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics