Skip to main content
Log in

Abstract

This paper presents the design and performance of a body-machine-interface (BoMI) system, where a user controls a robotic 3D virtual wheelchair with the signals derived from his/her shoulder and elbow movements. BoMI promotes the perspective that system users should no longer be operators of the engineering design but should be an embedded part of the functional design. This BoMI system has real-time controllability of robotic devices based on user-specific dynamic body response signatures in high-density 52-channel sensor shirt. The BoMI system not only gives access to the user’s body signals, but also translates these signals from user’s body to the virtual reality device-control space. We have explored the efficiency of this BoMI system in a semi-cylinderic 3D virtual reality system. Experimental studies are conducted to demonstrate, how this transformation of human body signals of multiple degrees of freedom, controls a robotic wheelchair navigation task in a 3D virtual reality environment. We have also presented how machine learning can enhance the interface to adapt towards the degree of freedoms of human body by correcting the errors performed by the user.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  1. Edwards, K., McCluskey, A.: A survey of adult power wheelchair and scooter users. Disabil. Rehabil. Assist. Technol. 5(6), 411–419 (2010)

    Article  Google Scholar 

  2. Clifton, D.W.: Paying for power. Rehab. Manag. 17, 32–36 (2004)

    Google Scholar 

  3. Fitzgerald, S.G., Kelleher, Teodorski, E.A., Collins, D.M., Boninger, M., Cooper, R.A.: The development of a nationwide registry of wheelchair users. Disabil. Rehabil. Assist. Technol. 2, 358–365 (2007)

    Article  Google Scholar 

  4. Miles-Tapping, C., MacDonald, L.J.: Lifestyle implications of power mobility. Phys. Occup. Ther. Geriatr. 12(4), 31–49 (1995)

    Article  Google Scholar 

  5. Pettersson, I., Törnquist, K., Ahlström, G.: The effect of an outdoor powered wheelchair on activity and participation in users with stroke. Disabil. Rehabil. Assist. Technol. 1(4), 235–243 (2006)

    Article  Google Scholar 

  6. Mortenson, W.B., Miller, W.C., Boily, J., Steele, B., Odell, L., Crawford, E.M., Desharnais, G.: Perceptions of power mobility use and safety within residential facilities. Can. J. Occup. Ther. Revue canadienne d’ergothérapie 72(3), 142 (2005)

    Article  Google Scholar 

  7. Cooper, E., Fyfe, N.C.M., Booth, S., Mandy, A., Broadbridge, H., Mortimer, C., Steedman, W.M., McMillan I.R., Ravey, J., Whiteford, G.E., et al.: The provision of powered wheelchairs: one year on. Int. J. Ther. Rehabil. 5(6), 280–281 (1998)

    Google Scholar 

  8. Brandt, A., Iwarsson, S., Stahle, A.: Older people’s use of powered wheelchairs for activity and participation. J. Rehab. Med. 36(2), 70–77 (2004)

    Article  Google Scholar 

  9. Fehr, L., Langbein, W.E., Skaar, S.B.: Adequacy of power wheelchair control interfaces for persons with severe disabilities: a clinical survey. J. Rehabil. Reserv. Dev. 37(3), 353–360 (2000)

    Google Scholar 

  10. Nitz, J.C.: Evidence from a cohort of able bodied adults to support the need for driver training for motorized scooters before community participation. Patient Educ. Couns. 70(2), 276–280 (2008)

    Article  Google Scholar 

  11. Hoenig, H., Pieper, C., Branch, L.G., Cohen, H.J.: Effect of motorized scooters on physical performance and mobility: a randomized clinical trial. Arch. Phys. Med. Rehab. 88(3), 279–286 (2007)

    Article  Google Scholar 

  12. Cassell, E., Clapperton, A.: Consumer product-related injury (2): Injury related to the use of motorised mobility scooters. Hazard (Ed. 62) Victorian Injury Surveillance Unit (2006)

  13. Velliste, M., Perel, S., Spalding, M.C., Whitford, A.S., Schwartz, A.B.: Cortical control of a prosthetic arm for self-feeding. Nature 453(7198), 1098–1101 (2008)

    Article  Google Scholar 

  14. Hochberg, L.R., Donoghue, J.P.: Sensors for brain-computer interfaces. IEEE Eng. Med. Biol. Mag. 25(5), 32–38 (2006)

    Article  Google Scholar 

  15. Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: Brain-computer interfaces for communication and control. Clin. Neurophysiol. 113(6), 767–791 (2002)

    Article  Google Scholar 

  16. Rebsamen, B., Burdet, E., Guan, C., Zhang, H., Teo, C.L., Zeng, Q., Ang, M., Laugier, C.: A brain-controlled wheelchair based on p300 and path guidance. In: The 1st International Conference on Biomedical Robotics and Biomechatronics (BioRob), pp. 1101–1106. IEEE (2006)

  17. McFarland, D.J., Krusienski, D.J., Sarnacki, W.A., and Wolpaw, J.R.: Emulation of computer mouse control with a noninvasive brain–computer interface. J. Neural Eng. 5, 101 (2008)

    Article  Google Scholar 

  18. Schalk, G., Miller, K.J., Anderson, N.R., Wilson, J.A., Smyth, M.D., Ojemann, J.G., Moran, D.W., Wolpaw, J.R., Leuthardt, E.C.: Two-dimensional movement control using electrocorticographic signals in humans. J. Neural Eng. 5, 75 (2008)

    Article  Google Scholar 

  19. Vidal, J.J.: Toward direct brain-computer communication. Annu. Rev. Biophys. Bio. 2(1), 157–180 (1973)

    Article  Google Scholar 

  20. Gotman, J., Gloor, P.: Automatic recognition and quantification of interictal epileptic activity in the human scalp eeg. Electroen. Clin. Neuro. 41(5), 513–529 (1976)

    Article  Google Scholar 

  21. Kandel, E.R., Schwartz, J.H., Jessell, T.M., et al.: Principles of Neural Science, vol. 4. McGraw-Hill New York (2000)

    Google Scholar 

  22. Lau, C., O’Leary, S.: Comparison of computer interface devices for persons with severe physical disabilities. Am. J. Occup. Ther. 47(11), 1022–1030 (1993)

    Article  Google Scholar 

  23. Yano, K., Hashimura, J., Aoki, T., Nishimoto, Y.: Flexion-extension motion assistance using an upper limb motion-assist robot based on trajectory estimation of reaching movement. In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 4599–4602. IEEE (2009)

  24. Kawamoto, H., Sankai, Y.: Power assist method based on phase sequence and muscle force condition for hal. Adv. Robot. 19(7), 717–734 (2005)

    Article  Google Scholar 

  25. Kiguchi, K., Rahman, M.H., Sasaki, M., Teramoto, K.: Development of a 3dof mobile exoskeleton robot for human upper-limb motion assist. Robot. Auton. Syst. 56(8), 678–691 (2008)

    Article  Google Scholar 

  26. Kobayashi, H., Nozaki, H., Tsuji, T.: Development of power assist system for caregiver by muscle suit. In: International Conference on Mechatronics and Automation (ICMA), pp. 180–185. IEEE (2007)

  27. Mao, Y., Agrawal, S.K.: Wearable cable-driven upper arm exoskeleton-motion with transmitted joint force and moment minimization. In: IEEE International Conference on Robotics and Automation, (ICRA) 2010, pp. 4334–4339. IEEE (2010)

  28. Ohara, E., Watanabe, T., Oishi, T., Aoki, T., Nishimoto, Y., Yano, K.: Assistance control of wheelchair operation using active cast for the upper limb. In: IEEE International Conference on Robotics and Automation, (ICRA) 2011, pp. 2223–2228. IEEE (2011)

  29. Krebs, H.I., Ferraro, M., Buerger, S.P., Newbery, M.J., Makiyama, A., Sandmann, M., Lynch, D., Volpe, B.T., Hogan, N.: Rehabilitation robotics: pilot trial of a spatial extension for mit-manus. J. NeuroEng. Rehabil. 1(1), 5 (2004)

    Article  Google Scholar 

  30. Scilingo, E.P., Lorussi, F., Mazzoldi, A., De Rossi, D.: Strain-sensing fabrics for wearable kinaesthetic-like systems. IEEE Sens. J. 3(4), 460–467 (2003)

    Article  Google Scholar 

  31. Tognetti, A., Lorussi, F., Bartalesi, R., Quaglini, S., Tesconi, M., Zupone, G., De Rossi, D.: Wearable kinesthetic system for capturing and classifying upper limb gesture in post-stroke rehabilitation. J. NeuroEng. Rehabil. 2(1), 8 (2005)

    Article  Google Scholar 

  32. Bonato, P.: Advances in wearable technology and applications in physical medicine and rehabilitation. J. NeuroEng. Rehabil. 2(1), 2 (2005)

    Article  MathSciNet  Google Scholar 

  33. Lorussi, F., Rocchia, W., Scilingo, E.P., Tognetti, A., DeRossi, D.: Wearable redundant fabric-based sensors arrays for reconstruction of body segment posture. IEEE Sens. J. 4(6), 807–818 (2004)

    Article  Google Scholar 

  34. Lorussi, F., Scilingo, E.P., Tesconi, M., Tognetti, A., De Rossi, D.: Strain sensing fabric for hand posture and gesture monitoring. IEEE Trans. Inf. Technol. Biomed. 9(3), 372–381 (2005)

    Article  Google Scholar 

  35. Adelola, I.A., Cox, S.L., Rahman, A.: Adaptable virtual reality interface for powered wheelchair training of disabled children. In: Proc. 4th Int. Conf. Disability, Virtual Reality Assoc. Tech (2002)

  36. Klein, C.A., Huang, C.H.: Review of pseudoinverse control for use with kinematically redundant manipulators. IEEE T. Syst. Man Cy. 13(2), 245–250 (1983)

    Article  Google Scholar 

  37. Pearson, K.: On lines and planes of closest fit to systems of points in space. Philos. Mag. 2(6), 559–572 (1901)

    Article  Google Scholar 

  38. Hotelling, H.: Analysis of a complex of statistical variables into principal components. J. Educ. Psychol. 24(6), 417–441 (1933)

    Article  Google Scholar 

  39. Molfese, D.L.: Electrophysiological correlates of semantic features. J. Psycholinguist. Res. 14(3), 289–299 (1985)

    Article  Google Scholar 

  40. Méndez-Bértolo, C., Pozo, M.A., Hinojosa, J.A.: Word frequency modulates the processing of emotional words: convergent behavioral and electrophysiological data. Neurosci. Lett. 494(3), 250–254 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tauseef Gulrez.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gulrez, T., Tognetti, A. A Sensorized Garment Controlled Virtual Robotic Wheelchair. J Intell Robot Syst 74, 847–868 (2014). https://doi.org/10.1007/s10846-013-9839-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-013-9839-1

Keywords

Navigation