Funded PhD Opportunity

Quantitatively assessment of limb motion utilising wearable sensors in remote rehabilitation

Subject: Computer Science and Informatics


Summary

Background: The increasing growth of the aging population has put pressure on public services especially healthcare services. According to the report by Northern Ireland Statistics and Research Agency (NISRA), the figures show a consistent trend of growth in population aged over 85 (BelfastTelegraph.co.uk, 2019). The prevalence of chronic disease (e.g. stroke, multiple sclerosis) and may lead to increase of the limb disabilities (Sousa et al., 2009). To address the current need in reducing the hospital visits and risk of readmission, the home rehabilitation can be a viable solution (Bernocchi et al., 2016). The current challenges in home rehabilitation include the clinical interpretation of quantitative rehabilitation measures (e.g. motion sensing data obtained from inertial sensing unit) and understanding clients’ performance on prescribed tasks during home rehabilitation.

Project aim: The proposed system will utilise the sensing components from the clients’ mobile phone which saves the cost to purchase a motion monitoring sensor/system. There are two major aims of this project. One is to develop a mobile phone-based system which enables the clinicians to remotely assess clients’ limb movement. Secondly, the system is able to work as a single sensor-based rehabilitation exercise assessment platform to be used in home for remote rehabilitation with the ability to detect whether the prescribed home rehabilitation exercises have been correctly performed. Furthermore, a visualisation platform will be able to provide for clinicians with the insights of clients movement performance. Visualisations can be co-created with healthcare professionals and variants can be objectively assessed and compared using eye tracking analysis. Motion tracking algorithms will be developed to enable the limb motion tracking by utilising a single inertial sensing unit (a smart phone in this project). Machine learning models will be trained for the purpose of recognition of clinicians’ prescribed home based exercises for patients. This proposed research project aligns with the school research focus in the areas of healthcare and interdisciplinary research.

References:

BelfastTelegraph.co.uk. (2019). Growth in Northern Ireland's older population putting pressure on health and social services - BelfastTelegraph.co.uk. [online] Available at: https://www.belfasttelegraph.co.uk/news/northern-ireland/growth-in-northern-irelands-older-population-putting-pressure-on-health-and-social-services-38535101.html [Accessed 12 Nov. 2019].

Sousa, R., Ferri, C., Acosta, D., Albanese, E., Guerra, M., Huang, Y., Jacob, K., Jotheeswaran, A., Rodriguez, J., Pichardo, G., Rodriguez, M., Salas, A., Sosa, A., Williams, J., Zuniga, T. and Prince, M. (2009). Contribution of chronic diseases to disability in elderly people in countries with low and middle incomes: a 10/66 Dementia Research Group population-based survey. The Lancet, 374(9704), pp.1821-1830.

Bernocchi, P., Vanoglio, F., Baratti, D., Morini, R., Rocchi, S., Luisa, A. and Scalvini, S. (2016). Home-based telesurveillance and rehabilitation after stroke: a real-life study. Topics in Stroke Rehabilitation, 23(2), pp.106-115.


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)
  • Sound understanding of subject area as evidenced by a comprehensive research proposal

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.

  • Publications record appropriate to career stage
  • A comprehensive and articulate personal statement
  • Applicants will be shortlisted if they have an average of 75% or greater in a first (honours) degree (or a GPA of 8.75/10). For applicants with a first degree average in the range of 70% to 74% (GPA 3.3): If they are undertaking an Masters, then the average of their first degree marks and their Masters marks will be used for shortlisting.

Funding

    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:

    Vice Chancellors Research Studentship (VCRS)

    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.

    Vice-Chancellor’s Research Bursary (VCRB)

    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.

    Vice-Chancellor’s Research Fees Bursary (VCRFB)

    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.

    Department for the Economy (DFE)

    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


Other information


The Doctoral College at Ulster University


Reviews

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

Adrian Johnston - PhD in Informatics

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Key dates

Submission deadline
Friday 7 February 2020

Interview Date
Late March 2020


Applying

Apply Online  


Campus

Jordanstown campus

Jordanstown campus
The largest of Ulster's campuses


Contact supervisor

Dr Lu Bai


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