PhD Study : Video analysis of abnormal behaviours within smart environments (VAAB)

  • Funded PhD Opportunity
  • This opportunity is now closed.
  • Computing, Engineering and the Built Environment
Apply and key information  

Summary

Background:
With a growing elderly population, chronic health conditions, such as dementia, that require long-term care have become a major challenge for health and social care services. As dementia develops, it becomes common for a patient to exhibit behavioural symptoms in terms of agitation and aggression. Typical characteristics of these behaviours include repetitive movements or actions and restlessness (pacing up and down and fidgeting). These behavioural symptoms can distress patients and their carers. The ability to recognise the onset of these behaviours is therefore important, as it enables carers to intervene and deal with them promptly. For example, if the behaviours are caused by anxiety, research has shown that anxiety levels can be reduced by playing music.
Video technology offers opportunities to monitor behavioural trends and recognise events. In this project we will develop feature detection algorithms for video data that are designed specifically to recognise the symptoms associated with agitation and restlessness. These will include analysis of facial expression, body posture, and movements (particularly repetitive movements or actions). As well as using conventional video we will explore the use of thermal imaging to augment the data and analyse the usefulness of this additional modality for identifying onset of states of anxiety, agitation and aggression. We will also develop automated recognition based on the development and training of a Convolutional Neural Network, and explore how the network can be enhanced in a hybrid approach using specific features extracted from the video and thermal imaging data. Hence we will train a learning algorithm to recognise the onset of anxiety, providing the potential to alert a carer for early intervention.
Strategic fit with current research:
This project will extend existing research in the Pervasive Computing research group in the areas of assisted living and healthcare technologies. A number of collaborative projects in these areas have been funded by the Economic and Social Research Council (ESRC), the Alzheimer’s Association, and the Department of Employment & Learning NI (DEL NI). Specialised smart environment laboratory facilities are available, including video surveillance cameras and a range of other sensor devices.
Anticipated research outcomes:
This project will develop a state-of-the-art approach to the automated analysis of video data to recognise restlessness and anxiety, and hence provide the potential for an alert system that can assist carers to act promptly to minimise the distress of an elderly patient.
Synopsis:
This project investigates the representation and automated recognition of events in video relating to symptoms of agitation and anxiety. The research has the potential to enable a carer alert system that is based on video technology to assist in minimising patient distress.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

  • First Class Honours (1st) Degree
  • Masters at 70%

Funding and eligibility

The University offers the following levels of support:

Vice Chancellors Research Studentship (VCRS)

The following scholarship options are available to applicants worldwide:

  • Full Award: (full-time tuition fees + £19,000 (tbc))
  • Part Award: (full-time tuition fees + £9,500)
  • Fees Only Award: (full-time tuition fees)

These scholarships will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance) and will provide a £900 per annum research training support grant (RTSG) to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Please note: you will automatically be entered into the competition for the Full Award, unless you state otherwise in your application.

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £19,000 (tbc) 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 support grant (RTSG) allocation to help support the PhD researcher.

  • Candidates with pre-settled or settled status under the EU Settlement Scheme, who also satisfy a three year residency requirement in the UK prior to the start of the course for which a Studentship is held MAY receive a Studentship covering fees and maintenance.
  • Republic of Ireland (ROI) nationals who satisfy three years’ residency in the UK prior to the start of the course MAY receive a Studentship covering fees and maintenance (ROI nationals don’t need to have pre-settled or settled status under the EU Settlement Scheme to qualify).
  • Other non-ROI EU applicants are ‘International’ are not eligible for this source of funding.
  • Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies. Further information on cost of living

The Doctoral College at Ulster University

Key dates

Submission deadline
Monday 19 February 2018
12:00AM

Interview Date
9 to 23 March 2018

Preferred student start date
Mid September 2018

Applying

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Contact supervisor

Dr Shuai Zhang

Shuai Zhang

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