Skip to main content

Assisted Computer Interaction for Users with Weak Upper Limb Motion

  • Chapter
  • First Online:
Neuro-Robotics

Part of the book series: Trends in Augmentation of Human Performance ((TAHP,volume 2))

  • 2431 Accesses

Abstract

Computer assisted therapy is one of the most promising new techniques for those suffering from physical and neurological dysfunction. As a result recently there has been a considerable body of work directed towards the development of rehabilitation and power/motion coordination systems based on assistive robotic devices [1, 2]. These devices range from manipulandums and simple power orthoses to exoskeletal systems [3–13] and aim to assist in all areas of physical therapy, for instance, to recover from different injuries, to compensate for various disabilities, or to provide motion coordination/assistance and performance evaluation [14–24]. Some of these pathological conditions such as; Parkinson’s disease, Muscular Dystrophy, Muscle Ataxia and Cerebral Palsy have symptoms such as reduced strength, restricted or irregular (jerky) movements, poor motion coordination and a continuum of impairments involving spasms and tremors. Often these physical impairments can make it difficult or impossible for sufferers to interact with computer generated environments using conventional mouse type interfaces [25, 26] limiting their scope to take advantage of developments in computer technology for work, educational, entertainment and social purposes. This has a significant impact on life and work opportunities. Assistive robotic devices may help to ameliorate these difficulties for this group. For interactions with a computer generated environment, the efficacy of various human machine interfaces such as force feedback mouse [27, 28] has been evaluated in GUI interaction tasks. Velocity dependent force feedback has been evaluated in a number of other studies to damp erratic motions [29, 30]. It has been shown that increasing the viscous damping helps to reduce the level of sudden motions but at the same time resistance to voluntary movement may occur.

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
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover 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. Hillman M (2003) Rehabilitation robotics from past to present – a historical perspective. In: Proceedings of the international conference on rehabilitation robotics, Daejeon, Korea, April 2003

    Google Scholar 

  2. Burgar CG, Lum PS, Shor PC, Van der Loos HFM (2000) Development of robots for rehabilitation therapy: the Palo Alto VA/Stanford experience. J Rehabil Res Dev 37(6):663–673

    CAS  PubMed  Google Scholar 

  3. Oblak J, Cikajlo I, Matjacic Z (2010) Universal haptic drive: a robot for arm and wrist rehabilitation. IEEE Trans Neural Syst Rehabil Eng 18(3):293–302

    Article  PubMed  Google Scholar 

  4. Caldwell DG, Tsagarakis NG, Kousidou S, Costa N, Sarakoglou Y (2007) Soft’ exoskeletons for upper and lower body rehabilitation – design, control and testing. J Humanoid Robot: Spec Issue Act Exoskeleton 4(3):549–573

    Article  Google Scholar 

  5. Spencer SJ, Klein J, Minakata K, Le V, Bobrow JE, Reinkensmeyer DJ (2008) A low cost parallel robot and trajectory optimization method for wrist and forearm rehabilitation using the Wii. In: Proceedings of the 2008 IEEE EMBS conference on biorobot, 2008, Scottsdale, pp 869–874

    Google Scholar 

  6. Rosen M, Arnold A, Baiges I, Aisen M, Eglowstein S (1995) Design of a controlled-energy-dissipation-orthosis (CEDO) for functional suppression of intention tremors. J Rehabil Res Dev 32(1):1–16

    CAS  PubMed  Google Scholar 

  7. Brown M, Tsagarakis NG, Caldwell DG (2003) Exoskeletons for human force augmentation. Ind Robot 30(6):592–602

    Article  Google Scholar 

  8. Carignan CR, Naylor MP, Roderick SN (2008) Controlling shoulder impedance in a rehabilitation arm exoskeleton. In: Proceedings of the IEEE ICRA 2008, Pasadena, CA, pp 2453–2458

    Google Scholar 

  9. Tsagarakis NG, Caldwell DG (2003) Development and control of a ‘soft-actuated’ exoskeleton for use in physiotherapy and training. Auton Robot Spec Issue Rehabil Robot 15:21–33

    Article  Google Scholar 

  10. Kong K, Jeon D (2006) Design and control of an exoskeleton for the elderly and patients. IEEE/ASME Trans Mechatron 11(4):428–432

    Article  Google Scholar 

  11. Kousidou S, Tsagarakis NG, Caldwell DG, Smith C (2006) Assistive exoskeleton for task based physiotherapy in 3-dimensional space. In: Proceedings of the IEEE/RAS-EMBS international conference on biomedical robotics and biomechatronics, 2006 (BioRob 2006). Pisa, Italy, pp 266–271

    Google Scholar 

  12. Kousidou S, Tsagarakis NG, Smith C, Caldwell DG (2007) Task-orientated biofeedback system for the rehabilitation of the upper limb. In: Proceedings of the 10th international conference on rehabilitation robotics, (ICORR). Noordwijk, Netherlands, pp 376–384

    Google Scholar 

  13. Gupta A, O’Malley MK (2006) Design of a haptic arm exoskeleton for training and rehabilitation. IEEE/ASME Trans Mechatron 11:280–289

    Article  Google Scholar 

  14. Nef T, Mihelj M, Colombo G, Riener R (2006) ARMin – robot for rehabilitation of the upper extremities. In: Proceedings of the 2006 IEEE international conference on robotics and automation, Orlando, Florida, May 2006, pp 3152–3157

    Google Scholar 

  15. Kim DJ, H-Knudsen R, Culver-Godfrey H, Rucks G, Cunningham T, Portée D, Bricout J, Wang Z, Behal A (2012) How autonomy impacts performance and satisfaction: results from a study with spinal cord injured subjects using an assistive robot. IEEE Trans Syst Man Cybern A Syst Hum 42(1):2–14

    Article  Google Scholar 

  16. Rosati G, Gallina P, Masiero S (2007) Design, implementation and clinical tests of a wire-based robot for neurorehabilitation. Trans Neural Syst Rehabil Eng 15(4):560–569

    Article  Google Scholar 

  17. Kahn LE, Zygman ML, Rymer WZ, Reinkensmeyer DJ (2006) Robot-assisted reaching exercise promotes arm movement recovery in chronic hemiparetic stroke: a randomized controlled pilot study. J Neuroeng Rehabil 3:12

    Article  PubMed Central  PubMed  Google Scholar 

  18. Uemura M, Kanaoka K, Kawamura S (2006) Power assist system for sinusoidal motion by passive element and impedance control. In: Proceedings of the IEEE ICRA, Orlando, Florida, May 2006, pp 3935–3940

    Google Scholar 

  19. Volpe BT, Krebs HI, Hogan N et al (2000) A novel approach to stroke rehabilitation: robot-aided sensorimotor stimulation. Neurology 54(10):1938–1944

    Article  Google Scholar 

  20. Magee JJ, Betke M, Gips J, Scott MR, Waber BN (2008) A human–computer interface using symmetry between eyes to detect gaze direction. IEEE Trans Syst Man Cybern A Syst Hum 38(6):1248–1261

    Article  Google Scholar 

  21. Cesqui B, Micera S, Mazzoleni S, Carrozza MC, Dario P (2006) Analysis of upper limb performance of elderly people using a mechatronic system. In: Proceedings of the international conference on biomedical robotics and biomechatronics, Pisa, pp 365–370

    Google Scholar 

  22. Rocon E, Ruiz AF, Brunneti F, Pons JL (2006) On the use of an active wearable exoskeleton for tremor suppression via biomechanical loading. In: Proceedings of the 2006 IEEE international conference on robotics and automation, Orlando, Florida, May 2006. pp 3140–3145

    Google Scholar 

  23. Koeneman EJ, Schultz RS, Wolf SL, Herring DE, Koeneman JB (2004) A pneumatic muscle hand therapy device. Conf Proc IEEE Eng Med Biol Soc 4:2711–2713

    CAS  PubMed  Google Scholar 

  24. Krebs HI, Volpe BT, Williams D, Celestino J, Charles SK, Lynch D, Hogan N (2007) Robot-aided neurorehabilitation: a robot for wrist rehabilitation. IEEE Trans Neural Syst Rehabil Eng 15:327–335

    Article  PubMed Central  PubMed  Google Scholar 

  25. Trewin S, Pain H (1999) Keyboard and mouse errors due to motor disabilities. Int J Hum-Comput Stud 50(2):109–144

    Article  Google Scholar 

  26. Dennerlein JT, Yang MC (2001) Haptic force feedback devices for the office computer: performance and musculoskeletal loading issues. Hum Factors 43(2):278–286

    Article  CAS  PubMed  Google Scholar 

  27. Hasser S, Goldenberg C, Martin A, Rosenberg K (1998) User performance in a GUI pointing task with a low-cost force feedback computer mouse. In: Proceedings of the ASME Dynamic Systems and Control Division. American Society of Mechanical Engineers, New York, pp 151–156

    Google Scholar 

  28. Hwang F, Keates S, Langdon P, Clarkson PJ (2003) Multiple haptic targets for motion impaired users. In: Proceedings of the CHI 2003, Fort Lauderdale, pp 41–48

    Google Scholar 

  29. Beringhause S, Rosen M, Haung S (1989) Evaluation of a damped joystick for people disabled by intention tremor. In: Proceedings of the RESNA 12th annual conference, New Orleans, pp 41–42

    Google Scholar 

  30. Morrice B, Becker W, Hoffer J, Lee R (1990) Manual tracking performance in patients with cerebellar incoordination – effects of mechanical loading. Can J Neurol Sci 17(3):275–285

    CAS  PubMed  Google Scholar 

  31. Delatycki MB, Williamson R, Forrest SM (2000) Friedreich ataxia: an overview. J Med Genet 37:1–8

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  32. Milner TE, Cloutier C (1990) Damping of the wrist joint during voluntary movement. Exp Brain Res 122:309–317

    Article  Google Scholar 

  33. Becker JD, Mote CD (1990) Identification of a frequency response model of joint rotation. J Biomech Eng 112:1–8

    Article  CAS  PubMed  Google Scholar 

  34. Hajian AZ, Howe RD (1997) Identification of the mechanical impedance at the human finger tip. J Biomech Eng 119:109–114

    Article  CAS  PubMed  Google Scholar 

  35. Lacquaniti F, Licata F, Soechting JF (1982) The mechanical behaviour of the human forearm in response to transient perturbations. Biol Cybern 44:35–46

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nikos G. Tsagarakis Ph.D. .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Tsagarakis, N.G., Caldwell, D.G. (2014). Assisted Computer Interaction for Users with Weak Upper Limb Motion. In: Artemiadis, P. (eds) Neuro-Robotics. Trends in Augmentation of Human Performance, vol 2. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-8932-5_9

Download citation

Publish with us

Policies and ethics