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Authors: Gergely Magyar 1 ; João Balsa 2 ; Ana Cláudio 2 ; Maria Carmo 2 ; Pedro Neves 2 ; Pedro Alves 2 ; Isa Félix 3 ; Nuno Pimenta 4 and Mara Guerreiro 5

Affiliations: 1 Department of Cybernetics and Artificial Intelligence, Technical University of Kosice, Letna 9, Kosice and Slovakia ; 2 Biosystems & Integrative Sciences Institute (BioISI), Faculdade de Ciências da Universidade de Lisboa, Lisboa, Portugal ; 3 Unidade de Investigação e Desenvolvimento em Enfermagem (ui&de), Escola Superior de Enfermagem de Lisboa, Lisboa, Portugal ; 4 Sport Sciences School of Rio Maior – Polytechnic Institute of Santarém, Rio Maior, Portugal, Exercise and Health Laboratory, Interdisciplinary Centre for the Study of Human Performance, ULisboa, Cruz-Quebrada, Portugal ; 5 Unidade de Investigação e Desenvolvimento em Enfermagem (ui&de), Escola Superior de Enfermagem de Lisboa, Lisboa, Portugal, Centro de Investigação Interdisciplinar Egas Moniz (CiiEM), Instituto Universitário Egas Moniz, Monte de Caparica, Portugal

ISBN: 978-989-758-354-4

Keyword(s): Virtual Humans, Relational Agents, Artificial Intelligence, Health Care, Behaviour Change, Type 2 Diabetes, Older People.

Abstract: The global prevalence of diabetes is escalating. Attributable deaths and avoidable health costs related to diabetes represent a substantial burden and threaten the sustainability of contemporary healthcare systems. Information technologies are an encouraging avenue to tackle the challenge of diabetes management. Anthropomorphic virtual assistants designed as relational agents have demonstrated acceptability to older people and may promote long-term engagement. The VASelfCare project aims to develop and test a virtual assistant software prototype to facilitate the self-care of older adults with type 2 diabetes mellitus. The present position paper describes key aspects of the VASelfCare prototype and discusses the potential use of artificial intelligence. Machine learning techniques represent promising approaches to provide a more personalised user experience with the prototype, by means of behaviour adaptation of the virtual assistant to users’ preferences or emotions or to develop cha tbots. The effect of these sophisticated approaches on relevant endpoints, such as users’ engagement and motivation, needs to be established in comparison to less responsive options. (More)

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Paper citation in several formats:
Magyar, G.; Balsa, J.; Cláudio, A.; Carmo, M.; Neves, P.; Alves, P.; Félix, I.; Pimenta, N. and Guerreiro, M. (2019). Anthropomorphic Virtual Assistant to Support Self-care of Type 2 Diabetes in Older People: A Perspective on the Role of Artificial Intelligence.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP, ISBN 978-989-758-354-4, pages 323-331. DOI: 10.5220/0007572403230331

@conference{grapp19,
author={Gergely Magyar. and João Balsa. and Ana Paula Cláudio. and Maria Beatriz Carmo. and Pedro Neves. and Pedro Alves. and Isa Brito Félix. and Nuno Pimenta. and Mara Pereira Guerreiro.},
title={Anthropomorphic Virtual Assistant to Support Self-care of Type 2 Diabetes in Older People: A Perspective on the Role of Artificial Intelligence},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP,},
year={2019},
pages={323-331},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007572403230331},
isbn={978-989-758-354-4},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP,
TI - Anthropomorphic Virtual Assistant to Support Self-care of Type 2 Diabetes in Older People: A Perspective on the Role of Artificial Intelligence
SN - 978-989-758-354-4
AU - Magyar, G.
AU - Balsa, J.
AU - Cláudio, A.
AU - Carmo, M.
AU - Neves, P.
AU - Alves, P.
AU - Félix, I.
AU - Pimenta, N.
AU - Guerreiro, M.
PY - 2019
SP - 323
EP - 331
DO - 10.5220/0007572403230331

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