Design of a Glove Controlled by Electromyographic Signals for the Rehabilitation of Patients with Rheumatoid Arthritis

  • Conference paper
  • First Online:
Information and Communication Technologies (TICEC 2020)

Abstract

Among the various systemic disorders that hands can suffer, rheumatoid arthritis is one of the most common. This disease affects the synovial tissue of the joints, making extension and flexion movements difficult. Currently, there are drugs on the market to treat it, but they produce dangerous side effects affecting the quality of life of the patient. In this context, physical rehabilitation plays an important role as a complement to the work of conventional medications. The present work describes the hand rehabilitation device that can be used to improve the mobility of people with rheumatoid arthritis. This glove shaped device can move all five fingers, using the measurement of the action potential of other healthy muscles. The data collection is done through a muscle sensor which processes the signal and sends the order to the glove, allowing contraction or relaxation of the hand. The glove was designed in 3D using the Fusion 360 software. In this case, this device captures the movements of patterns generated in a muscle and reproduces them in the fingers of the hand to increase the level of movement and prevent muscle atrophy in patients with this disease.

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

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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 EPUB and 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 ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Steinberg, D.: Overview of Hand Disorders - Bone, Joint, and Muscle Disorders - MSD Manual Consumer Version (2020). https://www.msdmanuals.com/home/bone,-joint,-and-muscle-disorders/hand-disorders/overview-of-hand-disorders

  2. The British Society for Surgery of the Hand Disorders. https://www.bssh.ac.uk/patients/conditions/hand_disorders. Accessed 25 June 2020

  3. Rheumatoid Arthritis by the Numbers: Facts, Statistics, and You. https://www.healthline.com/health/rheumatoid-arthritis/facts-statistics-infographic#4

  4. Dugowson, C.: Rheumatoid arthritis. In: Women and Health, pp. 674–685. Academic Press, Cambridge (2000). https://doi.org/10.1016/B978-012288145-9/50062-0

  5. Kontzias, A.: Rheumatoid arthritis (RA) (2020). https://www.msdmanuals.com/professional/musculoskeletal-and-connective-tissue-disorders/joint-disorders/rheumatoid-arthritis-ra?query=RheumatoidArthritis(RA)

  6. Institute for Quality and Efficiency in Health Care: Rheumatoid Arthritis: Overview (2006). https://www.ncbi.nlm.nih.gov/books/NBK384455/

  7. Freeman, J.: RA Facts: What are the Latest Statistics on Rheumatoid Arthritis? (2018). https://www.rheumatoidarthritis.org/ra/facts-and-statistics/

  8. Ksiȩzopolska-Orłowska, K., Sadura-Sieklucka, T., Kasprzak, K., et al.: The beneficial effects of rehabilitation on hand function in patients with rheumatoid arthritis. Rheumatology 54, 285–290 (2016). https://doi.org/10.5114/reum.2016.64903

    Article  Google Scholar 

  9. Krabak, B., Minkoff, E.: Rehabilitation Management for the Rheumatoid Arthritis Patients from Johns Hopkins Arthritis. https://www.hopkinsarthritis.org/patient-corner/disease-management/rehabilitation-management-rheumatoid-arthritis-patients/#orthoses

  10. Novak, D.: Biomechatronic applications of brain-computer interfaces. In: Handbook of Biomechatronics, pp. 129–175. Elsevier, Amsterdam (2019). https://doi.org/10.1016/B978-0-12-812539-7.00008-8

  11. Electromyography (EMG) - Mayo Clinic. https://www.mayoclinic.org/tests-procedures/emg/about/pac-20393913

  12. Lamkin-Kennard, K.A., Popovic, M.B.: Sensors: natural and synthetic sensors. In: Biomechatronics, pp. 81–107. Elsevier, Amsterdam (2019). https://doi.org/10.1016/b978-0-12-812939-5.00004-5

  13. Lopez-Olivo, M.A., Siddhanamatha, H.R., Shea, B., et al.: Methotrexate for treating rheumatoid arthritis. Cochrane Database Syst. Rev. (2014). https://doi.org/10.1002/14651858.CD000957.pub2

    Article  Google Scholar 

  14. Smolen, J.S., Landewé, R., Bijlsma, J., et al.: EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2016 update. Ann. Rheum. Dis. 76, 960–977 (2017). https://doi.org/10.1136/annrheumdis-2016-210715

    Article  Google Scholar 

  15. Fleischmann, R., Mysler, E., Hall, S., et al.: Efficacy and safety of tofacitinib monotherapy, tofacitinib with methotrexate, and adalimumab with methotrexate in patients with rheumatoid arthritis (ORAL Strategy): a phase 3b/4, double-blind, head-to-head, randomized controlled trial. Lancet 390, 457–468 (2017). https://doi.org/10.1016/S0140-6736(17)31618-5

    Article  Google Scholar 

  16. Combe, B.: Progression in early rheumatoid arthritis. Best Pract. Res. Clin. Rheumatol. 23, 59–69 (2009). https://doi.org/10.1016/j.berh.2008.11.006

    Article  Google Scholar 

  17. Ong, C.K.S., Lirk, P., Tan, C.H., Seymour, R.A.: An evidence-based update on nonsteroidal anti-inflammatory drugs. Clin. Med. Res. 5, 19–34 (2007). https://doi.org/10.3121/cmr.2007.698

    Article  Google Scholar 

  18. Beyermann, K., Jacobs, C., Prommersberger, K.J., Lanz, U.: Die präoperative intermittierende pneumatische dehnungsbehandlung bei ausgeprägter Dupuytrenscher kontraktur. Handchirurgie Mikrochirurgie Plast Chir 34, 118–122 (2002). https://doi.org/10.1055/s-2002-32305

    Article  Google Scholar 

  19. Chua, M.C.H., Hoon, L.J., Yeow, R.C.H.: Design and evaluation of Rheumatoid Arthritis rehabilitative Device (RARD) for laterally bent fingers. In: Proceeding of IEEE RAS EMBS International Conference on Biomed Robot Biomechatronics, July 2016, pp. 839–843 (2016). https://doi.org/10.1109/BIOROB.2016.7523732

  20. Abdallah, I., Bouteraa, Y., Rekik, C.: Design and development of 3D printed myoelectric robotic exoskeleton for hand rehabilitation. Int. J. Smart Sens. Intell. Syst. 10(2), 341–366 (2017). https://doi.org/10.21307/ijssis-2017-215

  21. Thingiverse, MakerBot. https://www.thingiverse.com/thing:2799056. Accessed 21 June 2020

  22. Geizans, R.: Develo** 3D Printed Prosthetic Hand Model Controlled by EMG Signal from Forearm (2018)

    Google Scholar 

  23. Kotkar, T., Masure, P., Modake, P., et al.: Modeling and testing of spur gear made of different 3D printed materials, pp. 1389–1394 (2018)

    Google Scholar 

  24. Aslanzadeh, S., Saghlatoon, H., Honari, M.M., et al.: Investigation on electrical and mechanical properties of 3D printed Nylon 6 for RF/microwave electronics applications. Addit. Manuf. (2018). https://doi.org/10.1016/j.addma.2018.02.016

    Article  Google Scholar 

  25. Ortiz, J., Tonato, G.: Anthropometric evaluation of hands in students of the physical therapy career of the PUCE for the elaboration of a database applied in the redesign of an exoskeleton, 33–41 (2018)

    Google Scholar 

  26. Herath, H.M.C.M., Gopura, R.A.R.C., Lalitharatne, T.D.: An underactuated linkage finger mechanism for hand prostheses, 121–139 (2018). https://doi.org/10.4236/mme.2018.82009

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to G. F. Villalba-Meneses .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Aguiar Salazar, E.D. et al. (2020). Design of a Glove Controlled by Electromyographic Signals for the Rehabilitation of Patients with Rheumatoid Arthritis. In: Rodriguez Morales, G., Fonseca C., E.R., Salgado, J.P., Pérez-Gosende, P., Orellana Cordero, M., Berrezueta, S. (eds) Information and Communication Technologies. TICEC 2020. Communications in Computer and Information Science, vol 1307. Springer, Cham. https://doi.org/10.1007/978-3-030-62833-8_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-62833-8_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62832-1

  • Online ISBN: 978-3-030-62833-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Navigation