Implementation of various control algorithms for hand rehabilitation exercise using wearable robotic hand | Intelligent Service Robotics Skip to main content
Springer Nature Link
Log in

Implementation of various control algorithms for hand rehabilitation exercise using wearable robotic hand

  • Original Research
  • Published:
Intelligent Service Robotics Aims and scope Submit manuscript

Abstract

In this paper, the control algorithms for strength exercise using wearable robotic hand are reviewed and the experimental results are analyzed and discussed. The SNU Exo-Glove is a soft exoskeleton that actuates motor function in disabled hands. This new type of device comprises a jointless simple mechanical structure and is actuated with wires. The strength exercise algorithms include isotonic, isokinetic, and impedance control exercises. An electromyography (EMG) regulation algorithm is proposed to limit the maximum level of activation of the muscles to prevent injury of the muscles and joints. The tension of the wire and the sEMG signal are analyzed to validate the effectiveness of rehabilitation with SNU Exo-Glove.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Chandrapal M, Chen X (2009) Intelligent active assistive and resistive orthotic device for knee rehabilitation. In: IEEE international conference on control and automation, pp 1880–1885

  2. Westlake K, Patten C (2009) Pilot study of Lokomat versus manual-assisted treadmill training for locomotor recovery post-stroke. J NeuroEng Rehabil 6(18)

  3. Housman SJ, Scott KM, Reinkensmeyer DJ (2009) A randomized controlled trial of gravity-supported, computer-enhanced arm exercise for individuals with severe hemiparesis. Neurorehabil Neural Repair 23(5):505–514

    Article  Google Scholar 

  4. Nef T, Mihelj M, Kiefer G, Perndl C, Muller R, Riener R (2007) ARMin-exoskeleton for arm therapy in stroke patients. In: 2007 IEEE 10th international conference on rehabilitation, robotics, pp 68–74

  5. Wege A, Hommel G (2005) Development and control of a hand exoskeleton for rehabilitation of hand injuries. In: IEEE/RSJ international conference on intelligent robots and systems, pp 3046–3051

  6. Wang J, Li J, Zhang Y, Wang S (2009) Design of an exoskeleton for index finger rehabilitation. In: 31st Annual international conference of the IEEE EMBS, pp 5957–5960

  7. DiCicco M, Lucas L, Matsuoka Y (2004) Comparison of control strategies for an EMG controlled orthotic exoskeleton for the hand. In: 2004 IEEE international conference on robotics and automation, vol 2, pp 1622–1627

  8. Hasegawa Y, Mikami Y, Watanabe K, Firouzimehr Z, Sankai Y (2008) Wearable handling support system for paralyzed patient. In: IEEE/RSJ international conference on intelligent robots and systems, pp 741–746

  9. In H-K, Cho K-J, Kim KR, Lee BS (2011) Jointless structure and under-actuation mechanism for compact hand exoskeleton. In: Proceeding of the IEEE international conference on rehabilitation, robotics, pp 1–6

  10. In H-K, Cho K-J (2012) Evaluation of the antagonistic tendon driven system for SNU Exo-Glove. In: The 9th international conference on ubiquitous robots and ambient, intelligence, pp 507–509

  11. Guilhem G, Cornu C, Guevel A (2011) Muscle architecture and EMG activity changes during isotonic and isokinetic eccentric exercises. Eur J Appl Physiol 111(11):2723–2733

    Article  Google Scholar 

  12. Carignan CR, Tang J (2008) A haptic control interface for a motorized exercise machine. In: IEEE international conference on robotics and automation, pp 2055–2060

  13. Colombo R, Pisano F, Micera S, Mazzone A, Delconte C, Carrozza MC, Dario P, Minuco G (2005) Robotic techniques for upper limb evaluation and rehabilitation of stroke patients. IEEE Trans Neural Syst Rehabil Eng 13:311–324

    Article  Google Scholar 

  14. Wang D, Li J, Li C (2009) An adaptive haptic interaction architecture for knee rehabilitation robot. In: International conference on mechatronics and automation, pp 84–89

  15. Sin MK, Park DG, Cho KJ (2011) Comparison and evaluation of robotic strength rehabilitation algorithms: isokinetic, isotonic and shared control method. In: Proceeding of the international conference on advanced mechatronic systems (ICAMechS), pp 438–441

  16. Guilhem Gael, Cornu Christophe, Guevel Arnaud (2011) Muscle architecture and EMG activity changes during isotonic and isokinetic eccentric exercises. Eur J Appl Physiol 111(11):2723–2733

    Article  Google Scholar 

  17. Hogan N (1985) Impedance control: an approach to manipulation-Part I: theory; Part II: implementation; Part III: applications. Trans ASME J Dyn Syst Measure Control 107(1):1–24

    Article  MATH  Google Scholar 

  18. Peer A, Buss M (2008) A new admittance-type haptic interface for bimanual manipulations. IEEE/ASME Trans Mechatron 13(4):416–428

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2010-0013470) and the Technology Innovation Program (100036459, 10036492) funded by the MKE/KEIT, Korea.

Author information

Authors and Affiliations

  1. School of Mechanical and Aerospace Engineering/IAMD, Seoul National University, Seoul, 151-742, Korea

    Useok Jeong, Hyun-Ki In & Kyu-Jin Cho

Authors
  1. Useok Jeong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hyun-Ki In
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kyu-Jin Cho
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kyu-Jin Cho.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jeong, U., In, HK. & Cho, KJ. Implementation of various control algorithms for hand rehabilitation exercise using wearable robotic hand. Intel Serv Robotics 6, 181–189 (2013). https://doi.org/10.1007/s11370-013-0135-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11370-013-0135-5

Keywords

Search

Navigation