Skip to main content

Application of Surface Electromyographic Signals for Electric Rotor Control

  • Conference paper
  • First Online:
Mechatronics 2017 - Ideas for Industrial Applications (MECHATRONICS 2017)

Abstract

The aim of this study was to develop an algorithm to control an electric rotor using surface electromyographic (sEMG) signals. The paper presents a design of an automated mechatronic robot for rehabilitation of both upper and lower limbs. Due to the implemented controller it is possible to program exercises in full spectrum and with various loads.

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 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
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. Zembaty, A.: Kinezyterapia. Tom 1. Zarys podstaw teoretycznych I diagnostyka kinezyterapii. Wydawnictwo KASPER (2015)

    Google Scholar 

  2. Kiwerski, J. (ed.): Rehabilitacja Medyczna. Wydawnictwo Lekarskie PZWL, Warszawa (2005)

    Google Scholar 

  3. Paśniczek, R.: Bioinżynieria w rehabilitacji narządu ruchu. Oficyna Wydawnicza Politechniki Warszawskiej, Warszawa (2014)

    Google Scholar 

  4. Kruse, R., Gebhardt, J., Klawonn, F.: Foundations of Fuzzy Systems. Wiley, Hoboken (1994)

    MATH  Google Scholar 

  5. del Boca, A., Park, D.C.: Myoelectric signal recognition using fuzzy clustering and artificial neural networks in real time. In: IEEE International Conference on Neural Networks and IEEE World Congress on Computational Intelligence, vol. 5, pp. 3098–3103 (1994)

    Google Scholar 

  6. Popkorn, S.: First Steps in Modal Logic. Cambridge University Press, Cambridge (1994)

    Book  Google Scholar 

  7. Erdmann, W.S.: Inżynieria rehabilitacji ruchowej. Wydawnictwo Politechniki Gdańskiej (2016)

    Google Scholar 

  8. Kazuo, K., Yoshiaki, H.: An EMG-based control for an upper-limb power-assist exoskeleton robot. IEEE Trans. Syst. Man Cybern. – Part B: Cybern. 42(4), 1064–1071 (2012)

    Article  Google Scholar 

  9. Ahmad, I., Ansari, F., Dey, U.K.: A review of EMG recording technique. Int. J. Eng. Sci. Technol. 4(2), 530–539 (2012)

    Google Scholar 

  10. Wege, A., Zimmermann, A.: Electromyography (EMG) sensor based control for a hand exoskeleton. In: Proceedings of the 2007 IEEE International Conference on Robotics and Bio-mimetics, 15–18 December 2007, Sanya, China, pp. 1470–1475 (2007)

    Google Scholar 

  11. Roy, S.H., Luca, G.D., Cheng, M.S., Johansson, A., Gilmore, L.D., Luca, C.J.D.: Electro-mechanical stability of surface EMG sensors. J. Med. Bio. Eng. Comput. 45, 447–457 (2007)

    Article  Google Scholar 

  12. Jain, R.K., Datta, S., Majumder, S.: Design and control of an EMG driven IPMC based artificial muscle finger. In: Naik, G.N. (ed.) Computational Intelligence in Electromyography Analysis - A Perspective on Current Applications and Future Challenges. InTech. https://doi.org/10.5772/48814

  13. Lippold, O.C.J.: The relation between integrated action potentials in a human muscle and its isometric tension. J. Physiol. 117, 492–499 (1952)

    Article  Google Scholar 

  14. Milner-Brown, S.R.B.: The relation between the surface electromyogram and force. J. Physiol. (London) 246, 549–569 (1975)

    Article  Google Scholar 

  15. Woods, J.J., Bigland-Ritchie, B.: Linear and non-linear surface EMG/force relationships in human muscle. J. Phys. Med. 6, 287–299 (1982)

    Google Scholar 

  16. Komi, P.V., Buskirk, E.R.: Reproducibility of electromyographic measurements with inserted wire electrodes and surface electrodes. Electromyogr. Clin. Neurophysiol. 10, 357–367 (1970)

    Google Scholar 

  17. Roberts, T.J., Gabaldón, A.M.: Interpreting muscle function from EMG: lessons learned from direct measurements of muscle force. Integr. Comp. Biol. 48(2), 312–320 (2008). https://doi.org/10.1093/icb/icn056

    Article  Google Scholar 

  18. Hermens, H.J., et al.: European Recommendations for Surface ElectroMyoGraphy. Results of the SENIAM Project. ISBN 90-75452-15-2. http://seniam.org/sensor_location.htm

  19. Raez, M.B.I., Hussain, M.S., Mohd-Yasin, F.: Techniques of EMG signal analysis: detection, processing, classification and applications. J. Biol. Proc. Online 8, 11–35 (2006)

    Article  Google Scholar 

  20. Merlo, A., Farina, D.A.: Fast and reliable technique for muscle activity detection from surface EMG signals. IEEE Trans. Biomed. Eng. 50(3), 316–323 (2003). https://doi.org/10.1109/TBME.2003.808829

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Agnieszka Konopelska .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Konopelska, A., Jureczko, M. (2019). Application of Surface Electromyographic Signals for Electric Rotor Control. In: Åšwider, J., Kciuk, S., Trojnacki, M. (eds) Mechatronics 2017 - Ideas for Industrial Applications. MECHATRONICS 2017. Advances in Intelligent Systems and Computing, vol 934. Springer, Cham. https://doi.org/10.1007/978-3-030-15857-6_25

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-15857-6_25

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-15856-9

  • Online ISBN: 978-3-030-15857-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics