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Development of personalised services and applications for healthcare

The Internet of Things (IoT) is becoming a reality and is increasingly getting more integrated in our everyday lives. Its interplay with Mobile Computing is a key ingredient in this. Smartphones are equipped with a range of sensors (gyroscope, accelerometer, GPS, etc.) which when combined with sensors that can be deployed, for instance, in a home setting (e.g. proximity, ambiance, motion, etc.) can offer improved monitoring and decision-making.

Such smart home network applications have been around for awhile, but are mainly targeted at energy management, security, monitoring, and detecting incidents.

There is little research exploring the potential and successful adoption of these applications for chronic self-management of health. This research will investigate the design, development and evaluation of such personalised services and applications for chronic disease management by integrating applications of Mobile Computing, IoT and Machine Learning.

Candidates should have good software/prototype design and development skills, and good hardware skills. Knowledge of networking technologies, Machine Learning, and experience in carrying out user-centred research and collecting and analysing both qualitative and quantitative data are also desirable.

How to apply

If you are interested in applying for the above PhD topic please follow the steps below:

  1. Contact the supervisor by email or phone to discuss your interest and find out if you woold be suitable. Supervisor details can be found on this topic page. The supervisor will guide you in developing the topic-specific research proposal, which will form part of your application.
  2. Click on the 'Apply here' button on this page and you will be taken to the relevant PhD course page, where you can apply using an online application.
  3. Complete the online application indicating your selected supervisor and include the research proposal for the topic you have selected.

Good luck!

This is a self funded topic

Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: https://www.brunel.ac.uk/research/Research-degrees/Research-degree-funding. The UK Government is also offering Doctoral Student Loans for eligible students, and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.

Meet the Supervisor(s)


Fotios Spyridonis - Fotis is a Lecturer in Computer Science focusing on Human-Computer Interaction (HCI) and Multimedia. 

George Ghinea - I am a Professor in the Department of Computer Science at Brunel University London. I obtained my BSc. Degree with Computer Science and Mathematics majors from the University of the Witwatersrand, South Africa. I later went on to obtain BSc. (Hons.) and MSc. Degrees, both in Computer Science, from the same university. I was awarded my PhD – Quality of Perception: An Essential Facet of Multimedia Communications -  from the University of Reading, UK, in 2000. In it, I proposed the Quality of Perception metric, a precursor of the Quality of Experience (QoE) concept now widely known. However, whilst QoE is still a concept, QoP is a concrete metric. Thus, recognising the infotainment duality of multimedia, QoP not only characterises the subjective enjoyment associated with experiencing multimedia presentations, but also how such presentations aid a person\'s ability to assimilate informational content. My research activities lie at the confluence of Computer Science, Media and Psychology. In particular, my work focuses on the area of perceptual multimedia quality and how one builds end-to-end communication systems incorporating user perceptual requirements. I have applied my expertise in areas such as eye-tracking, telemedicine, multi-modal interaction, and ubiquitous and mobile computing. I am particularly interested in building human-centred e-systems, particularly integrating human perceptual requirements. My work has been funded by both national and international funding bodies – all of it being collaborative work with other teams and stakeholders I have been privileged to be involved with. I have also been honoured to supervise 33 PhD students to completion and to have published over 350 high-quality research articles with them and other research collaborators. Currently, my research pursuits are centered on extending the notion of multimedia with that of mulsemedia – a term which I have put forward to denote multiple sensorial media, ie. media applications that go beyond engaging the by now traditional auditory and visual senses, engaging three of our other human in a realistic manner akin to our experiences of everyday life.

Zidong Wang - Zidong Wang is a member of Academia Europaea, a Member of the European Academy of Sciences and Arts, an IEEE Fellow and Professor of Computing at Brunel University London, UK. He has research interests in intelligent data analysis, statistical signal processing and dynamic systems & control. He has been named as the Hottest Scientific Researcher in 2012 in the area of Big Data and listed as highly cited researchers in categories of both computer science and engineering in 2015-2020 with an h-index of 139. He is currently serving as the Editor-in-Chief for International Journal of Systems Science, the Editor-in-Chief for Neurocomputing, the Editor-in-Chief for Systems Science and Control Engineering, and Associate Editor for other 12 prestigious journals including 5 IEEE Transactions.  His research has been funded by the EU, the Royal Society and the EPSRC. 

Xiaohui Liu - Xiaohui Liu is Professor of Computing at Brunel University London where he conducts research in artificial intelligence, data science and optimisation, with applications in diverse areas including biomedicine and engineering. Professor Liu has been named as a Highly Cited Researcher in Computer Science, Engineering, and Cross-Field (Clarivate/Web of Science).

Related Research Group(s)

Interactive Multimedia Systems

Interactive Multimedia Systems - Building sensor and media-rich, cross-layer, inclusive e-systems, with an interest in human-machine interaction, sensorial-based interfaces, data visualisation and multimedia.