This opportunity is now closed.

Funded PhD Opportunity

Enhancing Wearable Technologies through Artificial Intelligence.

Subject: Computer Science and Informatics


The rise of Wearable Technology has brought with it new approaches, more efficient processes, and innovative products in entertainment, manufacturing, transport, and many other areas. No other field, however, has higher expectations than healthcare (Amft, 2018). With applications ranging from lifestyle monitoring and disease prevention to chronic patient management. Over the last two decades, we have witnessed a transition from bulky carry-on electronics to smartphones and now computing technologies which are seamlessly integrated within everyday accessories, clothes, and body patches (Amft, 2017). Medical professionals and engineers have begun to integrate wearable technology in diagnosis and care pathways, validating their effectiveness with patients in large observational studies and randomized controlled trials.

Despite this, general uptake of wearable technology within healthcare has been limited, particularly with older adults (Cleland, 2016). Indeed, many current wearables have demonstrated critical issues with robustness (Banos, 2015) and compliance (Cleland, 2018). Research to address the current technical and practical challenges faced by wearable technologies is required to reach the true potential of improved health outcomes and more personalized prevention and care.

The aim of this project is to investigate how state-of-the-art wearable technologies may be utilised to support and improve the lives of older adults. In doing the project with address key challenges around technology adoption and how sustained engagement could be achieved. This will require the development and application of artificial intelligence to facilitate the capture, processing, validation, visualisation and interpretation of data from wearable devices.

The objectives of this research are to:

1)Investigate the barriers to adoption of wearable technology by older adults and how these can be modelled to provide insight into sustained engagement.

2)Review and critically evaluate the state-of-the-art in wearable sensing, what can be measured and how these measurements can be improved/refined.

3)Develop and evaluate technological solutions drawing on the advancements in Artificial Intelligence to enhance user engagement with wearable solutions.

4)Integrate wearable platforms with a range of devices within the IoT to extend and improve functionality.

This project will be aligned with the aims of the Connected Health Living Lab (CH:LL) and the Connected Health Innovation Centre (CHIC) at Ulster.

Amft, Oliver, and Kristof Van Laerhoven. "What Will We Wear After Smartphones?." IEEE Pervasive Computing 4 (2017): 80-85.

Amft, Oliver. "How Wearable Computing Is Shaping Digital Health." IEEE Pervasive Computing 1 (2018): 92-98.

Banos, O., Damas, M., Guillen, A., Herrera, L.J., Pomares, H., Rojas, I., Villalonga C. Multi-sensor fusion based on asymmetric decision weighting for robust activity recognition. Neural Processing Letters, vol. 42, no. 1, pp. 5-26 (2015)

Cleland, I., Nugent, C. and Lee, S., 2016, May. The ground truth is out there: challenges with using pervasive technologies for behavior change. In Proceedings of the 10th EAI International Conference on Pervasive Computing Technologies for Healthcare (pp. 322-325). ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering).

Cleland, I., M. P. Donnelly, C. D. Nugent, J. Hallberg, M. Espinilla, and M. Garcia-Constantino. "Collection of a Diverse, Realistic and Annotated Dataset for Wearable Activity Recognition." In 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp. 555-560. IEEE, 2018.

Essential criteria

  • Upper Second Class Honours (2:1) Degree or equivalent from a UK institution (or overseas award deemed to be equivalent via UK NARIC)


    Vice Chancellors Research Scholarships (VCRS)

    The scholarships will cover tuition fees and a maintenance award of £14,777 per annum for three years (subject to satisfactory academic performance). Applications are invited from UK, European Union and overseas students.


    The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £ 14,777 per annum for three years. EU applicants will only be eligible for the fees component of the studentship (no maintenance award is provided).  For Non EU nationals the candidate must be "settled" in the UK.

Other information

The Doctoral College at Ulster University


As Senior Engineering Manager of Analytics at Seagate Technology I utilise the learning from my PhD ever day

Adrian Johnston - PhD in Informatics

Watch Video  

Key dates

Submission deadline
Monday 18 February 2019

Interview Date
25 to 29 March 2019


Apply Online


Jordanstown campus

Jordanstown campus
The largest of Ulster's campuses

Contact supervisor

Dr Ian Cleland

Other supervisors

Related Funded Opportunities in: Computer Science and Informatics ,


Computer Science and Informatics

 View Details

Intelligent Systems

Computer Science and Informatics

 View Details

CHIC: Behavioural modelling based on opportunistic sensing techniques within IoT (Computing)

Closing date:
Monday 25 November 2019
Computer Science and Informatics

 View Details

Computer vision for advertising analytics

Closing date:
Friday 29 November 2019
Computer Science and Informatics

 View Details