Skip to main content
Book cover

International Conference on Intelligent Robotics and Applications

ICIRA 2019: Intelligent Robotics and Applications pp 439–446Cite as

Wrist Motor Function Rehabilitation Training and Evaluation System Based on Human-Computer Interaction

  • 1931 Accesses

Part of the Lecture Notes in Computer Science book series (LNAI,volume 11741)

Abstract

Based on human-computer interaction, a wrist motor function rehabilitation training and evaluation system is developed for the treatment or improvement of wrist motor dysfunction. Specifically, the joint angle sensor and the MYO wristband are used to realize the perception of the wrist motion on the ROS, the wrist motor function rehabilitation training game with information feedback is designed, and the quantitative evaluation on the wrist motor function is realized. The experimental results demonstrate that in the rehabilitation training session, the online accuracy of wrist motion recognition is 95.2%, and in the evaluation session, the root mean square error of the measured and actual values of the wrist joint angle is less than 5°. The paper works provide the basis for further clinical experiments of the wrist motor function rehabilitation training and evaluation.

Keywords

  • Human-computer interaction
  • ROS
  • Wrist motor function evaluation
  • Rehabilitation training

Research supported by the National Natural Science Foundation of China (61473265, 61803344), the Post-doctoral Funding in Henan province (001703041) and the Innovation Research Team of Science & Technology of Henan Province (17IRTSTHN013).

This is a preview of subscription content, access via your institution.

Chapter
GBP   19.95
Price includes VAT (United Kingdom)
  • DOI: 10.1007/978-3-030-27532-7_39
  • Chapter length: 8 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
GBP   67.99
Price includes VAT (United Kingdom)
  • ISBN: 978-3-030-27532-7
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
GBP   84.99
Price includes VAT (United Kingdom)
Learn about institutional subscriptions
Fig. 1.
Fig. 2.
Fig. 3.

References

  1. Pandian, S., Arya, K.N., Davidson, E.W.R.: Comparison of Brunnstrom movement therapy and motor relearning program in rehabilitation of post-stroke hemiparetic hand: a randomized trial. J. Bodywork Mov. Ther. 16(03), 330–337 (2012)

    CrossRef  Google Scholar 

  2. Serrien, D.J., Strens, L.H., Cassidy, M.J., et al.: Functional significance of the ipsilateral hemisphere during movement of the affected hand after stroke. Exp. Neurol. 190(02), 425–432 (2004)

    CrossRef  Google Scholar 

  3. Tsoupikova, D., Stoykov, N.S., Corrigan, M., et al.: Virtual immersion for post-stroke hand rehabilitation therapy. Ann. Biomed. Eng. 43(02), 467–477 (2015)

    CrossRef  Google Scholar 

  4. Hasani, F.N., MacDermid, J.C., Tang, A., Kho, M.E.: Cross-cultural adaptation and psychometric testing of the Arabic version of the Patient-Rated Wrist Hand Evaluation (PRWHE-A) in Saudi Arabia. J. Hand Ther. 28(4), 412–420 (2015)

    CrossRef  Google Scholar 

  5. Kennedy, S.A., Stoll, L.E., Lauder, A.S.: Human and other mammalian bite injuries of the hand: evaluation and management. J. Am. Acad. Orthop. Surg. 23(1), 47–57 (2015)

    CrossRef  Google Scholar 

  6. Thielbar, K.O., Lord, T.J., Fischer, H.C., et al.: Training finger individuation with a mechatronic-virtual reality system leads to improved fine motor control post-stroke. J. Neuroengineering Rehabil. 11(01), 171 (2014)

    CrossRef  Google Scholar 

  7. Rivas, J.J., Heyer, P., et al.: Towards incorporating affective computing to virtual rehabilitation; surrogating attributed attention from posture for boosting therapy adaptation. In: International Symposium on Medical Information Processing and Analysis, vol. 92(87), 58–63 (2015)

    Google Scholar 

  8. Heuser, A., Kourtev, H., Hentz, V., et al.: Tele-rehabilitation using the Rutgers Master II glove following Carpal Tunnel Release surgery. In: International Workshop on Virtual Rehabilitation, vol. 15(01), pp. 88–93 (2007)

    Google Scholar 

  9. Sucar, L.E., Orihuela, E.F., Velazquez, R.L., et al.: Gesture therapy: an upper limb virtual reality-based motor rehabilitation platform. IEEE Trans. Neural Syst. Rehabil. Eng. 22(03), 634–643 (2014)

    CrossRef  Google Scholar 

Download references

Author information

Affiliations

  1. School of Electrical Engineering, Zhengzhou University, Zhengzhou, Henan, China

    Haichuan Ren, Qi Song & Yanhong Liu

Authors
  1. Haichuan Ren
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qi Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yanhong Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yanhong Liu .

Rights and permissions

Reprints and Permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Ren, H., Song, Q., Liu, Y. (2019). Wrist Motor Function Rehabilitation Training and Evaluation System Based on Human-Computer Interaction. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11741. Springer, Cham. https://doi.org/10.1007/978-3-030-27532-7_39

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-27532-7_39

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27531-0

  • Online ISBN: 978-3-030-27532-7

  • eBook Packages: Computer ScienceComputer Science (R0)