This opportunity is now closed.

Funded PhD Opportunity

Artificial Intelligence for Smart Sensing to facilitate better health

Subject: Computer Science and Informatics


Summary

Wearable Sensors are a category of computing devices that can be worn by a user, and used to facilitate activity and physiological based measurements.  Wearable sensors can include multiple types of sensors, such as accelerometers, GPS trackers and heart rate monitors, combined into small form factor and integrated into garments or straps that can be worn. In the past, wearable sensors were only a tool used in research labs. However, the prevalence of wearable sensors in everyday life and introduction of new technologies has dramatically increased in the last decade. Smartphone and smartwatches are widespread and equipped with multiple sensors.

Similarly, fitness trackers are popular; elite sports athletes are wearing movement trackers with new wearable sports products being released annually. This advancement of wearable sensing technologies alongside embedded systems and wireless communication technologies makes it possible to now develop smart systems to monitor activities and people’s behaviour continuously.

Continuous monitoring of activities and of behaviour has enabled the development of a number of different applications, particularly in the area of health. Data extracted from wearable and ambient sensors can be analysed to extract health measurements and/or make predictions about future health risks. For example, wearable sensors can be used to measure a person’s walking patterns and data extracted can be used to measure the likelihood that person may be frail and/or have a fall in the near future [1].

Similarly, data can be used to analyse patterns of physical activity of a person and give advice on changes in behaviour which would be beneficial to the persons health [2]. Wearable sensors are also finding increased usage in elite sports where, for example, in Rugby Union sensors are worn on the players backs to track running and collisions with the aim of reducing injury and improving performance [3]. With the increase in the number of sensors and the population percentage wearing them, the amount of available data recorded is increasing exponentially. While data is plentiful, this data is useless unless we can extract some meaning from the data.

This project will make use of this data in an intelligent way - developing smart Artificial Intelligence techniques in order to better understand and extract meaning from wearable data. The project will specifically focus on developing Artificial Intelligence techniques that can extract health-related information from raw sensor data.

Techniques used will include machine learning, signal processing and pattern recognition. The overall goal will be to develop a system that utilized wearable sensors to extract indicators of health conditions such that screening of elderly patients can be performed in remote locations.

This project presents an exciting opportunity to work with cutting edge wearable sensors and have a potential positive impact on the elderly in rural communities.

This PhD is in alignment with multiple priorities arising from the NI Programme for Government Consultation especially regarding developing and implementing new policies and strategies within future healthcare provision. It is also aligned with Ulster’s strategic research themes of Sustainability (Digital Futures/Computing).


Essential criteria

  • To hold, or expect to achieve by 15 August, an Upper Second Class Honours (2:1) Degree or equivalent from a UK institution (or overseas award deemed to be equivalent via UK NARIC) in a related or cognate field.
  • Experience using research methods or other approaches relevant to the subject domain

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%
  • For VCRS Awards, Masters at 75%
  • Publications - peer-reviewed

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 support 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 support 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 support 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 support 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

Profile picture of Adrian Johnston

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
Monday 18 February 2019

Interview Date
19-20 March 2019


Applying

Apply Online  


Campus

Magee campus

Magee campus
A key player in the economy of the north west


Contact supervisor

Dr Joan Condell


Other supervisors

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