Is there an Optimal Technology to Provide Personal Supportive Feedback in Prevention of Obesity?

Simone Sandri, Huiru Zheng, Felix Engel, Anne Moorhead, Haiying Wang, Raymond Bond, Mike Mctear, Andrea Molinari, Paolo Bouquet, Matthias Hemmje

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Obesity is a global challenge that affects health and wellbeing worldwide. In this position paper, we review the digital technology used in prevention of obesity and present the proposed STOP project that integrates state-of-the-art wearable technology, chatbot, gamification data fusion, and machine learning with the aim to provide personalised supportive feedback for preventing obesity and maintaining healthy weight. Implication of sensitive data with General Data Protection Regulation (GDPR) is discussed. We conclude that machine learning plays an important role in data fusion, analytics, and providing optimal messaging tailored design to support healthy weight.
Original languageEnglish
Title of host publication 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Place of Publication San Diego, CA, USA
Pages1-6
Number of pages5
ISBN (Electronic)978-1-7281-1867-3
DOIs
Publication statusPublished - 18 Nov 2019
Event2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) - San Diego, CA, USA
Duration: 18 Nov 201921 Nov 2019

Conference

Conference2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Period18/11/1921/11/19

Keywords

  • obesity
  • prevention
  • machine learning
  • chatbot
  • supportive personalised feedback
  • gamification
  • data fusion

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  • Cite this

    Sandri, S., Zheng, H., Engel, F., Moorhead, A., Wang, H., Bond, R., Mctear, M., Molinari, A., Bouquet, P., & Hemmje, M. (2019). Is there an Optimal Technology to Provide Personal Supportive Feedback in Prevention of Obesity? In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 1-6). https://doi.org/10.1109/BIBM47256.2019.8983405