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University of Reading Featured PhD Programmes

Technology to Assess Nutrition in Older Adults

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  • Full or part time
    Dr Hwang
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

Project Overview:

It is estimated that 3 million people in the UK are malnourished or at risk of malnutrition, and of those, a third are over the age of 65 and 93% live in the community. Malnutrition in older people has a significant impact on quality of life, and with the population worldwide growing older, this represents a global challenge.

One of the current challenges is that gathering accurate information about dietary intake from people living in the community can be difficult because people often mis-report what they are eating. A particular challenge is estimating portion sizes, that is, recording *how much* a person has had to eat and drink . Traditional methods of assessing portion size include weighing/measuring food and drink, or comparing a portion with reference photos or objects. These traditional methods can be burdensome and inaccurate, and additionally, the data is most often collected in written form for later entry into a computer.

The aim of this project is to design and evaluate a technology for capturing food portion sizes. The technology should be appropriate for older adults, be suitable for field deployment, and aim to minimise the burden associated with recording and analyzing the data. The project will investigate multiple methods of capturing portion sizes, which could include a software interface that supports older adults to enter portion sizes, or more automated methods where the technology estimates portion sizes without additional input from the person. The research will also involve comparative studies to research how various methods compare with each other and with traditional methods in terms of accuracy and ease of use, for example.

School of Systems Engineering, University of Reading:

The University of Reading is one of the UK’s 20 most research-intensive universities and is ranked in the world’s top 200 universities according to the 2013/14 Times Higher Education World University Rankings. Achievements include the Queen’s Award for Export Achievement (1989) and the Queen’s Anniversary Prize for Higher Education (1998, 2006 and 2009). The School of Systems Engineering has a strong reputation for its innovative research in computer science and information systems, cybernetics, and electronic engineering. Our research is highly-regarded nationally and internationally, with demonstrated real-world impact.

Eligibility:

Applicants should have a bachelors (at least 2.1 or equivalent) or masters degree in Computer Science, Engineering, Human Computer Interaction or a strongly-related discipline. Strong programming and interpersonal skills are essential. Experience in user-centred design and working with older adults are desirable.

How to apply:

(1) Submit an application for a PhD in Computer Science using the link below.
(2) After submitting your application you will receive an email to confirm receipt; email should be forwarded along with a covering letter and full CV to Dr Faustina Hwang ([email protected]).
(3) In the online application system, there is a section for “Research proposal” and a box that says “If you have already been in contact with a potential supervisor, please tell us who” – in this box, please enter “Dr. Faustina Hwang”.

Application Deadline:

Applications accepted all year round.

Further enquiries:
Dr. Faustina Hwang, email: [email protected]

Funding Notes

We welcome applications from self-funded students worldwide for this project.

Students from Brazil: we welcome and support applications for the Science Without Borders Scholarship (Ciência sem Fronteiras) - http://www.reading.ac.uk/sciencewithoutbordersscholarships.

References

[1] C. M. Timon, S. E. Forster, M. E. Barker, A. J. Godfrey, F. Hwang and E. A. Williams (2011). A comparison of younger v. older adults' ability to estimate food portion sizes. Proceedings of the Nutrition Society, 70, E51 doi:10.1017/S0029665111000917.

[2] Jon Noronha, Eric Hysen, Haoqi Zhang, and Krzysztof Z. Gajos. 2011. Platemate: crowdsourcing nutritional analysis from food photographs. In Proceedings of the 24th annual ACM symposium on User interface software and technology (UIST '11). ACM, New York, NY, USA, 1-12. DOI=10.1145/2047196.2047198 http://doi.acm.org/10.1145/2047196.2047198

[3] Beenish M. Chaudry, Kay H. Connelly, Katie A. Siek, and Janet L. Welch. Formative Evaluation of a Mobile Liquid Portion Size Estimation Interface for People with Varying Literacy Skills. Journal of Ambient Intelligence and Humanized Computing, pages 1-11, Sept 2012.

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