Skip to main content

FMRI Compatible Sensing Glove for Hand Gesture Monitoring

  • Chapter
Book cover Immersive Multimodal Interactive Presence

Abstract

Here we describe and validate a fabric sensing glove for hand finger movement monitoring. After a quick calibration procedure, and by suitably processing of the outputs of the glove, it is possible to estimate hand joint angles in real time. Moreover, we tested the fMRI compatibility of the glove and ran a pilot fMRI experiment on the neural correlates of handshaking during human-to-human and human-to-robot interactions. Here we describe how the glove can be used to monitor correct task execution and to improve modeling of the expected hemodynamic responses during fMRI experimental paradigms.

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 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 shipping worldwide - see info
Hardcover Book
USD 109.99
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. 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 

  2. Hidler, J., Hodics, T., Xu, B., Dobkin, B., Cohen, L.G.: MR compatible force sensing system for real-time monitoring of wrist moments during fMRI testing. J. Neurosci. Methods 155(2), 300–307 (2006)

    Article  Google Scholar 

  3. Liu, J., Dai, T., Elster, T., Sahgal, V., Brown, R., Yue, G.: Simultaneous measurement of human joint force, surface electromyograms, and functional MRI-measured brain activation. J. Neurosci. Methods 101(1), 49–57 (2000)

    Article  Google Scholar 

  4. Reithler, J., Reithler, H., van den Boogert, E., Goebel, R., van Mier, H.: Resistance-based high resolution recording of predefined 2-dimensional pen trajectories in an fMRI setting. J. Neurosci. Methods 152(1–2), 10–17 (2006)

    Article  Google Scholar 

  5. Tada, M., Kanade, T.: An MR-compatible optical force sensor for human function modeling. In: Medical Image Computing and Computer-Assisted Intervention—MICCAI 2004, pp. 129–136 (2004)

    Chapter  Google Scholar 

  6. James, G.A., He, G., Liu, Y.: A full-size MRI-compatible keyboard response system. NeuroImage 25(1), 328–331 (2005)

    Article  Google Scholar 

  7. Gassert, R., Moser, R., Burdet, E., Bleuler, H.: MRI/fMRI-compatible robotic system with force feedback for interaction with human motion. IEEE/ASME Trans. Mechatron. 11(2), 216–224 (2006)

    Article  Google Scholar 

  8. Vanello, N., Hartwig, V., Tesconi, M., Ricciardi, E., Tognetti, A., Zupone, G., Gassert, R., Chapuis, D., Sgambelluri, N., Scilingo, E.P., et al.: Sensing glove for brain studies: Design and assessment of its compatibility for fMRI with a robust test. IEEE/ASME Trans. Mechatron. 13(3), 345–354 (2008)

    Article  Google Scholar 

  9. Vanello, N., Bonino, D., Ricciardi, E., Tesconi, M., Scilingo, E., Hartwig, V., Tognetti, A., Zupone, G., Cutolo, F., Giovannetti, G., et al.: Neural correlates of human-robot handshaking. In: RO-MAN, pp. 555–561. IEEE, New York (2010)

    Google Scholar 

  10. Skopec, M.: A primer on medical device interactions with magnetic resonance imaging systems, Feb. 4, 1997, CDRH magnetic resonance working group. US Department of Health and Human Services, Food and Drug Administration. Center for Devices and Radiological Health, Updated May 23 17 (1997)

    Google Scholar 

  11. Schenck, J.F.: Safety of strong, static magnetic fields. J. Magn. Reson. Imaging 12(1), 2–19 (2000)

    Article  Google Scholar 

  12. Lüdeke, K., Röschmann, P., Tischler, R.: Susceptibility artefacts in NMR imaging. J. Magn. Reson. Imaging 3(4), 329 (1985)

    Article  Google Scholar 

  13. Sijbers, J., Den Dekker, A., Van Audekerke, J., Verhoye, M., Van Dyck, D.: Estimation of the noise in magnitude MR images. J. Magn. Reson. Imaging 16(1), 87–90 (1998)

    Article  Google Scholar 

  14. Rombouts, S., Barkhof, F., Hoogenraad, F., Sprenger, M., Valk, J., Scheltens, P.: Test-retest analysis with functional MR of the activated area in the human visual cortex. Am. J. Neuroradiol. 18(7), 1317 (1997)

    Google Scholar 

  15. Machielsen, W.C.M., Rombouts, S.A.R.B., Barkhof, F., Scheltens, P., Witter, M.P.: FMRI of visual encoding: reproducibility of activation. Hum. Brain Mapp. 9(3), 156–164 (2000)

    Article  Google Scholar 

  16. Carelli, L., Gaggioli, A., Pioggia, G., De Rossi, F., Riva, G.: Affective robot for elderly assistance. Stud. Health Technol. Inform. 144, 44 (2009)

    Google Scholar 

  17. Pioggia, G., Igliozzi, R., Ferro, M., Ahluwalia, A., Muratori, F., De Rossi, D.: An android for enhancing social skills and emotion recognition in people with autism. IEEE Trans. Neural Syst. Rehabil. Eng. 13(4), 507–515 (2005)

    Article  Google Scholar 

  18. Bird, G., Leighton, J., Press, C., Heyes, C.: Intact automatic imitation of human and robot actions in autism spectrum disorders. Proc. R. Soc. Lond. B, Biol. Sci. 274(1628), 3027 (2007)

    Article  Google Scholar 

  19. Sidner, C.L., Lee, C., Kidd, C.D., Lesh, N., Rich, C.: Explorations in engagement for humans and robots. Artif. Intell. 166(1–2), 140–164 (2005)

    Article  Google Scholar 

  20. Nehaniv, C.L., Dautenhahn, K., Kubacki, J., Haegele, M., Parlitz, C., Alami, R.: A methodological approach relating the classification of gesture to identification of human intent in the context of human-robot interaction. In: IEEE International Workshop on Robot and Human Interactive Communication. ROMAN 2005, pp. 371–377. IEEE, New York (2005)

    Chapter  Google Scholar 

  21. Lee, K.M., Jung, Y., Kim, J., Kim, S.R.: Are physically embodied social agents better than disembodied social agents?: The effects of physical embodiment, tactile interaction, and people’s loneliness in human-robot interaction. Int. J. Hum.-Comput. Stud. 64(10), 962–973 (2006)

    Article  Google Scholar 

  22. Basdogan, C., Ho, C.H., Srinivasan, M.A., Slater, M.: An experimental study on the role of touch in shared virtual environments. ACM Trans. Comput.-Hum. Interact. 7(4), 443–460 (2000)

    Article  Google Scholar 

  23. Giannopoulos, E., Eslava, V., Oyarzabal, M., Hierro, T., González, L., Ferre, M., Slater, M.: The effect of haptic feedback on basic social interaction within shared virtual environments. In: Haptics: Perception, Devices and Scenarios, pp. 301–307 (2008)

    Chapter  Google Scholar 

  24. Ernst, M.O., Banks, M.S.: Humans integrate visual and haptic information in a statistically optimal fashion. Nature 415(6870), 429–433 (2002)

    Article  Google Scholar 

  25. Montoya, P., Sitges, C.: Affective modulation of somatosensory-evoked potentials elicited by tactile stimulation. Brain Res. 1068(1), 205–212 (2006)

    Article  Google Scholar 

  26. Chaplin, W.F., Phillips, J.B., Brown, J.D., Clanton, N.R., Stein, J.L.: Handshaking, gender, personality, and first impressions. J. Pers. Soc. Psychol. 79(1), 110 (2000)

    Article  Google Scholar 

  27. Åtröm, J., Thorell, L.H., Holmlund, U., d’Elia, G.: Handshaking, personality, and psychopathology in psychiatric patients: A reliability and correlational study. Perceptual and motor skills (1993)

    Google Scholar 

  28. Zecca, M., Endo, N., Itoh, K., Imanishi, K., Saito, M., Nanba, N., Takanobu, H., Takanishi, A.: On the development of the bioinstrumentation system WB-1R for the evaluation of human-robot interaction-head and hands motion capture systems. In: 2007 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp. 1–6. IEEE, New York (2007)

    Chapter  Google Scholar 

  29. Wang, Z., Peer, A., Buss, M.: An HMM approach to realistic haptic human-robot interaction. In: Third Joint EuroHaptics Conference, 2009 and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. World Haptics 2009, pp. 374–379. IEEE, New York (2009)

    Chapter  Google Scholar 

  30. Sato, T., Hashimoto, M., Tsukahara, M.: Synchronization based control using online design of dynamics and its application to human-robot interaction. In: IEEE International Conference on Robotics and Biomimetics. ROBIO 2007, pp. 652–657. IEEE, New York (2007)

    Google Scholar 

  31. Yamato, Y., Jindai, M., Watanabe, T.: Development of a shake-motion leading model for human-robot handshaking. In: SICE Annual Conference, pp. 502–507. IEEE, New York (2008)

    Chapter  Google Scholar 

  32. Cox, R.W., et al.: AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput. Biomed. Res. 29(3), 162–173 (1996)

    Article  Google Scholar 

Download references

Acknowledgements

The authors wish to thank the MRI Laboratory at G. Monasterio Foundation in Pisa, Italy, coordinated by M. Lombardi. The authors are grateful to Eng. Paolo Bianchi, Fabrizio Cutolo, Giuseppe Zupone and Mario Tesconi for contributions to this work. This work was partly supported by the ImmerSence project within the 6th Framework Programme of the European Union, FET—Presence Initiative, contract number IST-2006-027141, see also www.immersence.info.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nicola Vanello .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag London Limited

About this chapter

Cite this chapter

Vanello, N. et al. (2012). FMRI Compatible Sensing Glove for Hand Gesture Monitoring. In: Peer, A., Giachritsis, C. (eds) Immersive Multimodal Interactive Presence. Springer Series on Touch and Haptic Systems. Springer, London. https://doi.org/10.1007/978-1-4471-2754-3_12

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-2754-3_12

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-2753-6

  • Online ISBN: 978-1-4471-2754-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics