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-management, self-assess and self-regulate important wellbeing factors, for example, people on the autism spectrum.
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 these emotions within varying contexts, when presented with different levels of granularity owing to the richness of the available sensors.
The research will target emotions relating to stress and anxiety, to provide interventions 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 look to make use of established intervention strategies for 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) computational 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 aligns with research priorities identified by the Bamford Centre for Mental Health and Wellbeing Autism Research Hub and could leverage existing collaborations with Clinical Psychology networks across the 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.
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.
As Senior Engineering Manager of Analytics at Seagate Technology I utilise the learning from my PhD ever day
Adrian Johnston - PhD in InformaticsWatch Video
Monday 18 February 2019
25 to 29 March 2019
The largest of Ulster's campuses
Monday 25 November 2019
Computer Science and Informatics