Skip to main content

Wearable Vibrotactile Biofeedback to Improve Human-Exoskeleton Compliance During Assisted Gait Training

  • Conference paper
  • First Online:
Converging Clinical and Engineering Research on Neurorehabilitation IV (ICNR 2020)

Part of the book series: Biosystems & Biorobotics ((BIOSYSROB,volume 28))

Included in the following conference series:

  • 1321 Accesses

Abstract

Biofeedback may accelerate post-stroke motor recovery during exoskeleton-assisted gait training. A wearable vibrotactile human-robot interaction (HRI)-based biofeedback is proposed to improve human-exoskeleton compliance during gait training assisted by an ankle-foot exoskeleton (AFE). A pre-post study with four healthy subjects was conducted to evaluate biofeedback training’s efficacy. Results show statistically significant improvements (p-value: 4.56e−4–0.03) in HRI torque outcomes and the participants felt motivated about training. Findings suggest that the proposed biofeedback can enhance human-robot compliance.

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 349.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 449.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 449.99
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

Similar content being viewed by others

References

  1. G. Morone et al., Rehabilitative devices for a top-down approach. Expert Rev. Med. Devices 16(3), 187–195 (2019)

    Article  Google Scholar 

  2. F. Tamburella et al., Influences of the biofeedback content on robotic post-stroke gait rehabilitation: electromyographic vs joint torque biofeedback. J. Neuroeng. Rehabil. 16(1), 95 (2019)

    Article  Google Scholar 

  3. O. Stoller, M. Waser, L. Stammler, C. Schuster, Evaluation of robot-assisted gait training using integrated biofeedback in neurologic disorders. Gait Posture 35(4), 595–600 (2012)

    Article  Google Scholar 

  4. G. Asín-Prieto et al., Haptic adaptive feedback to promote motor learning with a robotic ankle exoskeleton integrated with a video game. Front. Bioeng. Biotechnol. 8(February), 1–5 (2020)

    Google Scholar 

  5. C. Pinheiro, J.M. Lopes, J. Figueiredo, L.M. Gonçalves, C.P. Santos, Design and technical validation of a wearable biofeedback system for robotic-based gait rehabilitation, in 20th IEEE International Conference on Autonomous Robot Systems and Competitions (2020)

    Google Scholar 

Download references

Acknowledgements

This work has been supported by the FEDER Funds through the Programa Operacional Regional do Norte and national funds from Fundação para a Ciência e Tecnologia with the SmartOs project under Grant NORTE-01-0145-FEDER-030386, and under the national support to R&D units grant, through the reference project UIDB/04436/2020 and UIDP/04436/2020.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Cristiana Pinheiro .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Pinheiro, C., Figueiredo, J., Santos, C.P. (2022). Wearable Vibrotactile Biofeedback to Improve Human-Exoskeleton Compliance During Assisted Gait Training. In: Torricelli, D., Akay, M., Pons, J.L. (eds) Converging Clinical and Engineering Research on Neurorehabilitation IV. ICNR 2020. Biosystems & Biorobotics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-030-70316-5_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-70316-5_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-70315-8

  • Online ISBN: 978-3-030-70316-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics