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An Architecture for a Coaching System to Support Type 2 Diabetic Patients

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Book cover Ambient Intelligence—Software and Applications—13th International Symposium on Ambient Intelligence (ISAmI 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 603))

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Abstract

Diabetes mellitus type 2 (DMT2) is an increasing worrying disease that has become a major public health challenge over the last decades. It can have serious health consequences and lead to long-term health complications that greatly impact the quality of life of the diabetic patient. Therefore, it becomes vital to define supportive mechanisms that can decrease the effect of the different risk factors and at the same time provide knowledge on how to deal with DMT2 and rely on new mobile technologies to help manage the disease. The work here presented had the main goal to propose the architecture for a coaching system that supports the self-management of diabetes mellitus type 2 disease which is being developed in the context of the FoodFriend project, with the goal of stimulating the innovation in the continuous monitoring of the patients’ health. The coaching system here proposed aims to support both health managers and diabetic patients through the processing of food-intake and health data and provide actionable feedback that can improve the health condition of the patient. This includes the presentation of personalized recommendations and challenges adapted to patient current health condition and their motivation to change health behaviors. By doing so, we believe it will be possible to improve the patients’ self-management of their disease as well as decrease the risk of disease-related complications associated to DMT2.

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Notes

  1. 1.

    https://www.who.int/news-room/fact-sheets/detail/diabetes.

  2. 2.

    https://www.cdc.gov/chronicdisease/resources/publications/factsheets/nutrition.htm.

  3. 3.

    https://www.nhs.uk/conditions/obesity/causes/

  4. 4.

    https://itea4.org/project/food-friend.html.

  5. 5.

    https://www.who.int/news-room/fact-sheets/detail/healthy-diet.

  6. 6.

    https://www.kaggle.com/datasets/arashnic/fitbit.

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Acknowledgments

This research work was developed under the project Food Friend –“Autonomous and easy-to-use tool for monitoring of personal food intake and personalised feedback” (ITEA 18032), co-financed by the North Regional Operational Program (NORTE 2020) under the Portugal 2020 and the European Regional Development Fund (ERDF), with the reference NORTE-01-0247-FEDER-047381 and by National Funds through FCT (Fundação para a Ciência e a Tecnologia) under the project UI/DB/00760/2020 and the PhD grant number UI/BD/151485/2021.

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Authors and Affiliations

  1. Research Group On Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD), Institute of Engineering, Polytechnic of Porto, Porto, Portugal

    Diogo Martinho, Vítor Crista, João Carneiro & Goreti Marreiros

  2. Department of Community Medicine, Information and Health Decision Sciences (MEDCIDS), Faculty of Medicine, University of Porto, Porto, Portugal

    Andreia Pinto, José Diniz & Alberto Freitas

  3. Center for Health Technology and Services Research (CINTESIS), Faculty of Medicine, University of Porto, Porto, Portugal

    Andreia Pinto, José Diniz & Alberto Freitas

Authors
  1. Diogo Martinho
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  2. Vítor Crista
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  3. Andreia Pinto
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  4. José Diniz
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  5. Alberto Freitas
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  6. João Carneiro
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  7. Goreti Marreiros
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Corresponding author

Correspondence to Diogo Martinho .

Editor information

Editors and Affiliations

  1. Universitat Politècnica de València, Valencia, Valencia, Spain

    Vicente Julián

  2. ISEP/GECAD, Porto, Portugal

    João Carneiro

  3. Científico Universidad de Salamanca, AIR Institute Villamayor, Parque, Salamanca, Spain

    Ricardo S. Alonso

  4. Edificio I+D+i (24.2), University of Salamanca, Salamanca, Salamanca, Spain

    Pablo Chamoso

  5. Departamento de Informática, University of Minho, Braga, Portugal

    Paulo Novais

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Martinho, D. et al. (2023). An Architecture for a Coaching System to Support Type 2 Diabetic Patients. In: Julián, V., Carneiro, J., Alonso, R.S., Chamoso, P., Novais, P. (eds) Ambient Intelligence—Software and Applications—13th International Symposium on Ambient Intelligence. ISAmI 2022. Lecture Notes in Networks and Systems, vol 603. Springer, Cham. https://doi.org/10.1007/978-3-031-22356-3_16

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