Sensor rich pervasive environments continue to emerge, driven by developments in the Internet of Things, providing evermore cost-effective off-the-shelf sensing solutions for continuous, unobtrusive monitoring of user habits and activities of daily living .
These technologies have been deployed within environments to learn behaviour patterns, to infer personalised needs or to assess wellbeing, and to facilitate timely support via targeted technology interventions . Such technology offers particular opportunities to address the unmet needs of those people in society who find it difficult to self-manage, self-assess and self-regulate important wellbeing factors, for example, people with autism spectrum disorders.
This project aims to investigate emerging machine learning approaches to support monitoring and interpretation of human emotion based on data that is opportunistically sensed  at time critical instances. A key challenge lies in interpreting emotions within varying contexts and levels of granularity owing to the richness of the available sensors at a given time point. The research will target emotions relating to stress and anxiety, to provide a basis for self-intervention that empower users to recognise and regulate stressful episodes.
The research will investigate a range of environmental and wearable sensors to monitor key wellness factors via assessment of heart rate variability , in combination with Affective Computing techniques and important contextual factors (e.g. schedule, routine, dietary intake, deadlines, engagement with games, social media, etc.). The work will also determine the feasibility of embedding established intervention strategies for reducing negative emotional state, such as guided parasympathetic breathing.
The core objectives of this research will focus upon:
(1) opportunistically sensing the onset of an environmental stressor;
(2) modelling of the emotional responses;
(3) investigating multimodal and multidimensional approaches to deliver targeted interventions.
A use case available to the project surrounds in-situ mobile assistive technology to support young people on the autism spectrum as they commence University. Transitioning from Secondary School to University is a significant period in a young person’s life, in particular, for people with autism, who report difficulties in self-regulation of emotion, adjustment to changes in environment and routine, and who often cannot clearly interpret or communicate their feelings .
This research can leverage existing collaborations within Ulster’s Autism Hub and Clinical Psychology networks across Health Trusts. An identified route for participant engagement within the project exists via Ulster’s Student Support Centre. This proposal fits with the University’s strategic theme of Healthy Communities and closely aligns with the Pervasive Computing Research Group, focusing upon research within the areas of Activity Recognition, Behaviour Analysis and Affective Computing. The project benefits from access to a range of existing pervasive and wearable sensing technologies.
The supervisory team has expertise and experience in both the theory surrounding the work and its application to support people on the autism spectrum. 1.K. Connelly et al. (2017 "The Future of Pervasive Health," in IEEE Pervasive Comp, 16(1): 16-20. 2.Cook, D., & Das, S. (2012). Pervasive computing at scale, Pervasive and Mobile Computing, 8: 22-35. 3.Kemp, H., & Quintana, D. (2013) The relationship between mental and physical health: Insights from the study of heart rate variability, Journal of Psychophysiology, 89(3): 288-296. 4.Roggen, D. et al. (2013) Opportunistic human activity and context recognition, Computer, 46(2): 36-45. 5.Roleska, M., et al. (2018) Autism and the right to education in the EU, PLOS ONE 13(8): 1-17.
If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.
The University offers the following awards to support PhD study and applications are invited from UK, EU and overseas for the following levels of support:
Full award (full-time PhD fees + DfE level of maintenance grant + RTSG for 3 years).
This scholarship will cover full-time PhD tuition fees and provide the recipient with £15,000 maintenance grant per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training studentship grant (RTSG) allocation to help support the PhD researcher.
Part award (full-time PhD fees + 50% DfE level of maintenance grant + RTSG for 3 years).
This scholarship will cover full-time PhD tuition fees and provide the recipient with £7,500 maintenance grant per annum for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training studentship grant (RTSG) allocation to help support the PhD researcher.
Fees only award (PhD fees + RTSG for 3 years).
This scholarship will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance). This scholarship also comes with £900 per annum for three years as a research training studentship grant (RTSG) allocation to help support the PhD researcher.
The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £ 15,009 per annum for three years. EU applicants will only be eligible for the fee’s component of the studentship (no maintenance award is provided). For Non-EU nationals the candidate must be "settled" in the UK. This scholarship also comes with £900 per annum for three years as a research training studentship grant (RTSG) allocation to help support the PhD researcher.
Due consideration should be given to financing your studies; for further information on cost of living etc. please refer to: www.ulster.ac.uk/doctoralcollege/postgraduate-research/fees-and-funding/financing-your-studies
As Senior Engineering Manager of Analytics at Seagate Technology I utilise the learning from my PhD ever day
Adrian Johnston - PhD in InformaticsWatch Video
Friday 7 February 2020
Late March 2020
The largest of Ulster's campuses
Monday 2 December 2019
Subject: Computer Science and Informatics
When applying for this PhD opportunity please quote reference number: