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International Joint Conference on Ambient Intelligence

AmI 2013: Evolving Ambient Intelligence pp 13–22Cite as

Design and Field Evaluation of REMPAD: A Recommender System Supporting Group Reminiscence Therapy

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Part of the Communications in Computer and Information Science book series (CCIS,volume 413)

Abstract

This paper describes a semi-automated web-based system to facilitate digital reminiscence therapy for patients with mild-to-moderate dementia, enacted in a group setting. The system, REMPAD, uses proactive recommendation technology to profile participants and groups, and offers interactive multimedia content from the Internet to match these profiles. In this paper, we focus on the design of the system to deliver an innovative personalized group reminiscence experience. We take a user-centered design approach to discover and address the design challenges and considerations. A combination of methodologies is used throughout this research study, including exploratory interviews, prototype use case walkthroughs, and field evaluations. The results of the field evaluation indicate high user satisfaction when using the system, and strong tendency towards repeated use in future. These studies provide an insight into the current practices and challenges of group reminiscence therapy, and inform the design of a multimedia recommender system to support facilitators and group therapy participants.

Keywords

  • Reminiscence therapy
  • dementia
  • recommender systems
  • user interface

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Author information

Authors and Affiliations

  1. INSIGHT: Data Analytics Research Centre, Dublin City University, Ireland

    Yang Yang, Niamh Caprani, Adam Bermingham, Cathal Gurrin & Alan F. Smeaton

  2. Department of Speech & Language Therapy, Adelaide & Meath Hospital, Tallaght, Ireland

    Julia O’Rourke & Rónán Collins

Authors
  1. Yang Yang
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  2. Niamh Caprani
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  3. Adam Bermingham
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  4. Julia O’Rourke
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  5. Rónán Collins
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  6. Cathal Gurrin
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  7. Alan F. Smeaton
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Editor information

Editors and Affiliations

  1. Adaptive Information Cluster, School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland

    Michael J. O’Grady

  2. University of Birjand, Iran

    Hamed Vahdat-Nejad

  3. Peter L. Reichertz Institute for Medical Informatics, Braunschweig, Germany

    Klaus-Hendrik Wolf

  4. Department of Computer Science, University College Dublin, Belfield, Dublin 4, Ireland

    Mauro Dragone

  5. University of St Andrews, UK

    Juan Ye

  6. RWTH Aachen University, Germany

    Carsten Röcker

  7. School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland

    Gregory O’Hare

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© 2013 Springer International Publishing

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Cite this paper

Yang, Y. et al. (2013). Design and Field Evaluation of REMPAD: A Recommender System Supporting Group Reminiscence Therapy. In: O’Grady, M.J., et al. Evolving Ambient Intelligence. AmI 2013. Communications in Computer and Information Science, vol 413. Springer, Cham. https://doi.org/10.1007/978-3-319-04406-4_3

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  • DOI: https://doi.org/10.1007/978-3-319-04406-4_3

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04405-7

  • Online ISBN: 978-3-319-04406-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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