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