Ugail, H, Mackevicius, R, Hardy, M et al. (5 more authors) (2020) MotiVar: Motivating Weight Loss Through A Personalised Avatar. In: Proceedings of the 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA 2019). 2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), 26-28 Aug 2019, Island of Ulkulhas, Maldives. IEEE ISBN: 978-1-7281-2741-5 ISSN: 2573-3214 EISSN: 2573-3214
Abstract
This work aims to develop a personalised avatar based virtual environment for motivating weight loss and weight management. Obesity is a worldwide epidemic which has not only enormous resource impact for the healthcare systems but also has substantial health as well as a psychological effect among the individuals who are affected. We propose to tackle this issue via the development of a personalised avatar, the form of which can be adjusted to show the present and the future self of the individual. For the avatar design and development phase, we utilise a parametric based mathematical formulation derived from the solutions of a chosen elliptic partial differential equation. This method not only enables us to generate a parameterised avatar model, but it also allows us to quickly and efficiently create various avatar shapes corresponding to different body weights and even to different body postures.
Metadata
| Item Type: | Proceedings Paper |
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| Authors/Creators: |
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| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Healthcare (Leeds) > Nursing Adult (Leeds) |
| Funding Information: | Funder Grant number NIHR National Inst Health Research PB-PG-1215-20016 |
| Depositing User: | Symplectic Publications |
| Date Deposited: | 02 Mar 2020 10:33 |
| Last Modified: | 02 Mar 2020 10:33 |
| Status: | Published |
| Publisher: | IEEE |
| Identification Number: | 10.1109/skima47702.2019.8982405 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:157838 |

CORE (COnnecting REpositories)
CORE (COnnecting REpositories)