Skip to main content
SpringerLink
Log in

Sensitivity Analysis of a Parametric Hand Exoskeleton Designed to Match Natural Human Grasping Motion

  • Conference paper
Advances in Autonomous Robotics (TAROS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7429))

Included in the following conference series:

Abstract

This paper describes the simulated analysis of a fully scalable, parametrically designed hand exoskeleton previously developed as part of a stroke rehabilitation program within the Bristol Robotics Laboratory. The device is parametrically designed to match the location and trajectories of the joints within a normal healthy human hand. However, testing of fully scalable designs which can be custom fit to a person using parametric design can be costly, time consuming and potentially hazardous if ill-fitting. Here a method is presented which allows for the performance of a parametric design to be tested. A virtual mechanism with induced manufacturing tolerances is modelled and its interactions with the hand are simulated. The performance can then be assessed by the devices ability to achieve the objective trajectory within the simulation. The results show that for the designed hand exoskeleton, with a manufacturing tolerance of 0.2mm across parts the resulting average trajectory error is less than 0.2 degrees with an average tip error of less than 0.5 mm. The results also demonstrate that for a large tolerance of 1mm across all dimensions, the trajectory error can reach as high as 30.9 degrees. This result justifies the use of parametric design to develop mechanisms matching natural human motion. While the results are for a parametrically scalable hand exoskeleton, it is believed the methodology is applicable to any bio-compatible assistive device.

This work was supported by the University of the West of England, Faculty of Health and Life Sciences under the direction of Dr Kevin Foreman and an EPSRC Doctoral Training Apprenticeship.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. M. R. Laboratories. Merck manual geriatrics (1997), http://www.merck.com/mrkshared/mmg/home.jsp

  2. Tonkin, R.: Stroke statistics (2007), http://www.stroke.org

  3. Kwakkel, G., Kollen, B.J., van der Grond, J., Prevo, A.J.: Probability of regaining dexterity in the flaccid upper limb: Impact of severity of paresis and time since onset in acute stroke. Stroke 34(9), 2181–2186 (2003)

    Article  Google Scholar 

  4. Khaw, J.T.: Epidemiology of stroke. Journal of Neurology, Neurosurgery, and Psychiatry 61(4), 333–338 (1996)

    Article  Google Scholar 

  5. Wolf, P.A., Grotta, J.C.: Cerebrovascular disease. Circulation 102(90004), IV–75–IV–80 (2000)

    Google Scholar 

  6. Wade, D.: National clinical guidelines for stroke: London royal college of physicians (2000), www.rcplondon.ac.uk/resources/stroke-guidelines

  7. Napier, J.R.: The prehensile movements of the human hand. The Journal of Bone and Joint Surgery 38B(4), 902–913 (1956)

    Google Scholar 

  8. Landsmeer, J.M.F.: Power grip and precision handling. Annals of the Rheumatic Diseases 21(2), 164–170 (1962)

    Article  Google Scholar 

  9. Nordin, M., Frankel, V.H.: Basic biomechanics of the musculoskeletal system. Lippincott Williams I& Wilkins (2001)

    Google Scholar 

  10. Wing, A.M., Fraser, C.: The contribution of the thumb to reaching movements. The Quarterly Journal of Experimental Psychology 35, 297–309 (1983)

    Article  Google Scholar 

  11. Seo, N., Rymer, W., Kamper, D.: Altered digit force direction during pinch grip following stroke. Experimental Brain Research 202, 891–901 (2010)

    Article  Google Scholar 

  12. Lang, C.E., DeJong, S.L., Beebe, J.A.: Recovery of thumb and finger extension and its relation to grasp performance after stroke. Journal of Neurophysiology 102(1), 451–459 (2009)

    Article  Google Scholar 

  13. Carr, J.H., Shepherd, R.B.: A Motor Relearning Programme for Stroke. Aspen Publishers (1987)

    Google Scholar 

  14. Woldag, H., Hummelsheim, H.: Evidence-based physiotherapeutic concepts for improving arm and hand function in stroke patients. Journal of Neurology 249, 518–528 (2002)

    Article  Google Scholar 

  15. Takahashi, C., Der-yeghiaian, L., Le, V., Motiwala, R., Cramer, S.: Robot-based hand motor therapy after stroke. Brain 131(2), 425–437 (2008)

    Article  Google Scholar 

  16. Kwakkel, G., Kollen, B.J., Krebs, H.I.: Effects of robot-assisted therapy on upper limb recovery after stroke: A systematic review. Neurorehabilitation and Neural Repair 22(2), 111–121 (2008)

    Article  Google Scholar 

  17. Krebs, H., Hogan, N., Aisen, M.L., Volpe, B.: Robot-aided neurorehabilitation. IEEE Transactions on Rehabilitation Engineering 6(1), 75–87 (1998)

    Article  Google Scholar 

  18. Salman, B., Vahdat, S., Lambercy, O., Dovat, L., Burdet, E., Milner, T.: Changes in muscle activation patterns following robot-assisted training of hand function after stroke. In: International Conference on Intelligent Robots and Systems, pp. 5145–5150 (October 2010)

    Google Scholar 

  19. Bouzit, M., Burdea, G., Popescu, G., Boian, R.: The rutgers master ii - new design force-feedback glove. IEEE/ASME Transactions on Mechatronics 7(2), 256–263 (2002)

    Article  Google Scholar 

  20. Stergiopoulos, P., Fuchs, P., Laurgeau, C.: Design of a 2-finger hand exoskeleton for vr grasping simulation. In: EuroHaptics 2003 (2003)

    Google Scholar 

  21. Dicicco, M., Lucas, L., Matsuoka, Y.: Comparison of two control strategies for a muscle controlled orthotic exoskeleton for the hand. In: IEEE International Conference on Robotics and Automation, pp. 1622–1627 (2004)

    Google Scholar 

  22. Mulas, M., Folgheraiter, M., Gini, G.: An emg-controlled exoskeleton for hand rehabilitation. In: International Conference on Rehabilitation Robotics, pp. 371–374 (2005)

    Google Scholar 

  23. Wege, A., Kondak, K., Hommel, G.: Mechanical design and motion control of a hand exoskeleton for rehabilitation. In: IEEE ICMA (2005)

    Google Scholar 

  24. Worsnopp, T., Peshkin, M., Colgate, J., Kamper, D.: Actuated finger exoskeleton for hand rehabilitation following. In: International Conference on Rehabilitation Robotics, pp. 896–901 (2007)

    Google Scholar 

  25. Fu, Y., Wang, P., Wang, S., Liu, H., Zhang, F.: Design and development of a portable exoskeleton based CPM machine for rehabilitation of hand injuries. In: International Conference on Robotics and Biomimetics, pp. 1476–1481 (2007)

    Google Scholar 

  26. Chiri, A., Giovacchini, F., Vitiello, N., Cattin, E., Roccella, S., Vecchi, F., Carrozza, M.: Handexos: Towards an exoskeleton device for the rehabilitation of the hand. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1106–1111 (October 2009)

    Google Scholar 

  27. Mohamaddan, S., Komeda, T.: Wire-driven mechanism for finger rehabilitation device, pp. 1015–1018 (2010)

    Google Scholar 

  28. Tong, K., Ho, S., Pang, P., Hu, X., Tam, W., Fung, K., Wei, X., Chen, P., Chen, M.: An intention driven hand functions task training robotic system. In: IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3406–3409 (September 2010)

    Google Scholar 

  29. de Araujo, R.C., Junior, F.L., Rocha, D.N., Sono, T.S., Pinotti, M.: Effects of intensive arm training with an electromechanical orthosis in chronic stroke patients: A preliminary study. Achives of Medical Rehabilitation 92, 1746–1753 (2011)

    Article  Google Scholar 

  30. Marvin, C.: Portable hand cpm w/soft splint 8091 (2007)

    Google Scholar 

  31. Takahashi, C., Le, V., Cramer, S.: A robotic device for hand motor therapy after stroke. Journal of Neurology, 17–20 (2005)

    Google Scholar 

  32. Burton, T., Vaidyanathan, R., Burgess, S., Turton, A., Melhuish, C.: A parameterized kinematic model of the human hand. In: Towards Autonomous Robotic Systems (TAROS), Plymouth, pp. 34–40 (September 2010)

    Google Scholar 

  33. Burton, T.M.W., Vaidyanathan, R., Burgess, S., Turton, A.J., Melhuish, C.: Development of a parametric kinematic model of the human hand and a novel robotic exoskeleton. In: IEEE International Conference on Rehabilitation Robotics (ICORR), Zurich (June 2011)

    Google Scholar 

  34. Pheasant, S., Haslegrave, C.M.: Bodyspace: Anthropometry, Ergonomics And The Design Of Work. Taylor I& Francis (October 2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Bristol Robotics Laboratory, University of Bristol, UK

    Thomas M. W. Burton, A. J. Turton & Chris Melhuish

  2. The University of the West of England, Frenchay Campus, UK

    Thomas M. W. Burton, A. J. Turton & Chris Melhuish

  3. Department of Mechanical Engineering, Imperial College, London, UK

    Ravi Vaidyanathan

  4. The Department of Systems Engineering, The US Naval Postgraduate School, Monterey, CA, USA, 93940

    Ravi Vaidyanathan

  5. Department of Mechanical Engineering, University of Bristol, UK

    Stuart C. Burgess

Authors
  1. Thomas M. W. Burton
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ravi Vaidyanathan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Stuart C. Burgess
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. A. J. Turton
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Chris Melhuish
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering and Bristol Robotics Laboratory, University of Bristol, Bristol, UK

    Guido Herrmann

  2. Intelligent Autonomous Systems Lab Faculty of Computing, Engineering & Mathematical Sciences, University of the West of England, BS16 1QY, Bristol, U.K.

    Matthew Studley

  3. University of the West of England, BS34 8QZ, Bristol, UK

    Martin Pearson , Andrew Conn  & Chris Melhuish ,  & 

  4. Department of Electrical and Electronic Engineering, Imperial College London, Exhibition Road, SW7 2BT, London, UK

    Mark Witkowski

  5. Robot Intelligence Technology Laboratory, Department of EECS, KAIST, Daejeon, Korea

    Jong-Hwan Kim

  6. National University of Singapore, Singapore

    Prahlad Vadakkepat

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Burton, T.M.W., Vaidyanathan, R., Burgess, S.C., Turton, A.J., Melhuish, C. (2012). Sensitivity Analysis of a Parametric Hand Exoskeleton Designed to Match Natural Human Grasping Motion. In: Herrmann, G., et al. Advances in Autonomous Robotics. TAROS 2012. Lecture Notes in Computer Science(), vol 7429. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32527-4_35

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-32527-4_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32526-7

  • Online ISBN: 978-3-642-32527-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation