Skip to main content
Springer Nature Link
Log in

Cognitive Assistant for Physical Exercise Monitoring in Hand Rehabilitation

  • Conference paper
  • First Online:
Fuzzy Logic and Technology, and Aggregation Operators (EUSFLAT 2023, AGOP 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14069))

  • 576 Accesses

Abstract

This paper introduces a novel, affordable companion robot that has been designed for rehabilitation purposes among the elderly population. The robot is equipped with a camera that records exercises, and an animation screen that delivers clear and easy-to-follow instructions and feedback. To evaluate the device, a machine learning algorithm was used on a dataset of therapy exercises. The results indicate that the robot effectively recognizes gestures and accurately identifies the exercises being performed. This study presents a groundbreaking and cost-effective solution for elderly rehabilitation and has the potential to revolutionize the industry with its cutting-edge technology.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Chen, Y., Wang, C., Lou, S.: Edge artificial intelligence camera network: an efficient object detection and tracking framework. J. Electron. Imaging 31(3), 033030–033030 (2022)

    Article  Google Scholar 

  2. Filho, C.P., et al.: A systematic literature review on distributed machine learning in edge computing. Sensors 22(7), 2665 (2022)

    Article  Google Scholar 

  3. Wei, Y., Gong, Z., Yang, S., Ye, K., Wen, Y.: EdgeCRNN: an edge-computing oriented model of acoustic feature enhancement for keyword spotting. J. Ambient Intell. Humanized Comput. 13, 1525–1535 (2022)

    Article  Google Scholar 

  4. McEnroe, P., Wang, S., Liyanage, M.: A survey on the convergence of edge computing and AI for UAVs: opportunities and challenges. IEEE Internet Things J. 9, 15435–15459 (2022)

    Article  Google Scholar 

  5. Fracasso, F., Buchweitz, L., Theil, A., Cesta, A., Korn, O.: Social robots acceptance and marketability in Italy and Germany: a cross-national study focusing on assisted living for older adults. Int. J. Soc. Robot. 14(6), 1463–1480 (2022)

    Article  Google Scholar 

  6. Stegner, L., Mutlu, B.: Designing for caregiving: Integrating robotic assistance in senior living communities. In: Designing Interactive Systems Conference, pp. 1934–1947 (2022)

    Google Scholar 

  7. Fischinger, D., et al.: Hobbit, a care robot supporting independent living at home: first prototype and lessons learned. Robot. Auton. Syst. 75, 60–78 (2016)

    Article  Google Scholar 

  8. Rincon, J.A., Julian, V., Carrascosa, C.: A physical cognitive assistant for monitoring hand gestures exercises. In: Ferrández Vicente, J.M., Álvarez-Sánchez, J.R., de la Paz López, F., Adeli, H. (eds.) IWINAC 2022. LNCS, vol. 13259, pp. 13–43. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-06527-9_2

    Chapter  Google Scholar 

  9. Perugia, G., Doladeras, M.D., Mallofré, A.C., Rauterberg, M., Barakova, E.: Modelling engagement in dementia through behaviour. Contribution for socially interactive robotics. In: 2017 International Conference on Rehabilitation Robotics (ICORR), pp. 1112–1117. IEEE (2017)

    Google Scholar 

  10. Moerman, C.J., Jansens, R.M.: Using social robot PLEO to enhance the well-being of hospitalised children. J. Child Health Care 25(3), 412–426 (2021)

    Article  Google Scholar 

  11. Šabanović, S., Bennett, C.C., Chang, W.L., Huber, L.: PARO robot affects diverse interaction modalities in group sensory therapy for older adults with dementia. In: 2013 IEEE 13th International Conference on Rehabilitation Robotics (ICORR), pp. 1–6. IEEE (2013)

    Google Scholar 

  12. Mannion, A., et al.: Introducing the social robot MARIO to people living with dementia in long term residential care: reflections. Int. J. Soc. Robot. 12, 535–547 (2020)

    Article  Google Scholar 

  13. Johnson, M.J., Mohan, M., Mendonca, R.: Therapist-patient interactions in task-oriented stroke therapy can guide robot-patient interactions. Int. J. Soc. Robot. 14(6), 1527–1546 (2022)

    Article  Google Scholar 

Download references

Acknowledgements

This work was partly supported by Universitat Politecnica de Valencia Research Grant PAID-10-19 and PID2021-123673OB-C31 funded by MCIN/AEI/ 10.13039/501100011033 and by “ERDFA way of making Europe”, Consellería d’Innovació, Universitats, Ciencia i Societat Digital from Comunitat Valenciana (APOSTD/2021/227) through the European Social Fund (Investing In Your Future) and grant from the Research Services of Universitat Politècnica de València (PAID-PD-22).

Author information

Authors and Affiliations

  1. Valencian Research Institute for Artificial Intelligence (VRAIN), Universitat Politècnica de València, Camino de Vera s/n, 46022, Valencia, Spain

    J. A. Rincon, C. Marco-Detchart, V. Julian & C. Carrascosa

  2. Valencian Graduate School and Research Network of Artificial Intelligence, Universitat Politècnica de València, Camí de Vera s/n, 46022, Valencia, Spain

    J. A. Rincon & V. Julian

Authors
  1. J. A. Rincon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. C. Marco-Detchart
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. V. Julian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. C. Carrascosa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J. A. Rincon .

Editor information

Editors and Affiliations

  1. University of the Balearic Islands, Palma, Spain

    Sebastia Massanet

  2. University of Oviedo, Gijón, Spain

    Susana Montes

  3. University of the Balearic Islands, Palma, Spain

    Daniel Ruiz-Aguilera

  4. University of the Balearic Islands, Palma, Spain

    Manuel González-Hidalgo

Rights and permissions

Reprints and permissions

Copyright information

© 2023 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

Rincon, J.A., Marco-Detchart, C., Julian, V., Carrascosa, C. (2023). Cognitive Assistant for Physical Exercise Monitoring in Hand Rehabilitation. In: Massanet, S., Montes, S., Ruiz-Aguilera, D., González-Hidalgo, M. (eds) Fuzzy Logic and Technology, and Aggregation Operators. EUSFLAT AGOP 2023 2023. Lecture Notes in Computer Science, vol 14069. Springer, Cham. https://doi.org/10.1007/978-3-031-39965-7_51

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-39965-7_51

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-39964-0

  • Online ISBN: 978-3-031-39965-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics