Skip to main content

Patient and Therapist Model Attributes for Social Robot Stroke Therapies Based on Implicit Knowledge from Expert Interviews

  • Conference paper
  • First Online:

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 310))

Abstract

Understanding what patients and therapists perceive may help to enhance social robots in rehabilitative therapies. In this paper we present the results of expert interviews about possible user model attributes for patients and therapists in stroke rehabilitation therapies. From these we derive implications for the use of social robots as therapist in these scenarios. As a method we asked therapists, about past patients and their impressions with other therapists in the post-stroke arm rehabilitation therapies of the E-BRAiN project. The interview technique was the repertory grid method, whereby we compare on a “between-subject” basis. The results show certain character traits and therapy-dependent characteristics, which can be used for the user modeling of both persons. We have found certain patient attributes to justify a system adaption like a “willingness for sabotage”.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   279.99
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

Learn about institutional subscriptions

References

  1. Quinn, S., Bond, R., Nugent, C.: Ontological modelling and rule-based reasoning for the provision of personalized patient education. Expert. Syst. 34, e12134 (2017). https://doi.org/10.1111/exsy.12134

    Article  Google Scholar 

  2. Ackerman, S.J., Hilsenroth, M.J.: A review of therapist characteristics and techniques positively impacting the therapeutic alliance. Clin. Psychol. Rev. 23, 1–33 (2003). https://doi.org/10.1016/s0272-7358(02)00146-0

    Article  Google Scholar 

  3. Winkle, K., Caleb-Solly, P., Turton, A., et al.: Social robots for engagement in rehabilitative therapies. In: Kanda, T., Ŝabanović, S., Hoffman, G., et al. (eds) Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction (pp 289–297). ACM, New York, NY, USA

    Google Scholar 

  4. Sáenz-de-Urturi, Z., Santos, O.C.L.: User modelling in exergames for frail older adults. In: Mitrovic, T., Zhang, J., Chen, L., et al. (eds) Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization (pp. 83–86). ACM, New York, NY, USA (2018)

    Google Scholar 

  5. Platz, T., Eickhof, C., van Kaick, S., et al.: Impairment-oriented training or Bobath therapy for severe arm paresis after stroke: a single-blind, multicentre randomized controlled trial. Clin. Rehabil. 19, 714–724 (2005). https://doi.org/10.1191/0269215505cr904oa

    Article  Google Scholar 

  6. Mirela Cristina, L., Matei, D., Ignat, B., et al.: Mirror therapy enhances upper extremity motor recovery in stroke patients. Acta Neurol. Belg. 115, 597–603 (2015). https://doi.org/10.1007/s13760-015-0465-5

    Article  Google Scholar 

  7. Platz, T., Lotze, M.: Arm ability training (AAT) promotes dexterity recovery after a stroke-a review of its design, clinical effectiveness, and the neurobiology of the actions. Front. Neurol. 9, 1082 (2018). https://doi.org/10.3389/fneur.2018.01082

    Article  Google Scholar 

  8. Trauzettel-Klosinski, S.: Aktuelle Möglichkeiten der visuellen Rehabilitation. Spektrum der Augenheilkunde 33, 89–104 (2019). https://doi.org/10.1007/s00717-019-0432-2

    Article  Google Scholar 

  9. Kelly, G.A.: Clinical diagnosis and psychotherapy, Reprinted. In: George, A.K. (eds.) The Psychology of Personal Constructs, Vol. 2. Routledge, London (2001)

    Google Scholar 

  10. Gaines, B.R., Shaw, M.L.G.: Knowledge acquisition tools based on personal construct psychology. Knowl. Eng. Rev. 8, 49–85 (1993). https://doi.org/10.1017/S0269888900000060

    Article  Google Scholar 

  11. Zhang, X., Han, H.: An empirical testing of user stereotypes of information retrieval systems. Inf. Process. Manage. 41, 651–664 (2005). https://doi.org/10.1016/j.ipm.2004.01.005

    Article  Google Scholar 

  12. GitHub: https://github.com/bunalex/rg-attributes. https://github.com/bunalex/rg-attributes. Accessed 20 Jan 2021 (2021)

  13. Winkle, K., Lemaignan, S., Caleb-Solly, P., et al.: Effective persuasion strategies for socially assistive robots. In: 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI) pp. 277–285. IEEE (2019)

    Google Scholar 

Download references

Acknowledgements

This joint research project “E-BRAiN—Evidence-based Robot Assistance in Neurorehabilitation” is supported by the European Social Fund (ESF), reference: ESF/14-BM-A55-0001/19-A01, and the Ministry of Education, Science and Culture of Mecklenburg-Vorpommern, Germany. The sponsors had no role in the decision to publish or any content of the publication.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alexandru Bundea .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bundea, A., Forbrig, P. (2022). Patient and Therapist Model Attributes for Social Robot Stroke Therapies Based on Implicit Knowledge from Expert Interviews. In: Zimmermann, A., Howlett, R.J., Jain, L.C. (eds) Human Centred Intelligent Systems. Smart Innovation, Systems and Technologies, vol 310. Springer, Singapore. https://doi.org/10.1007/978-981-19-3455-1_4

Download citation

Publish with us

Policies and ethics