Brain computer interface (BCI) to reduce risk of fall in older people

This project is part of a 4-year Dual PhD degree programme between the National Tsing Hua University (Taiwan) and the University of Liverpool (England). As part of the NTHU-UoL Dual PhD Award students are in the unique position of being able to gain 2 PhD awards at the end of their degree from two internationally recognised world-leading Universities. As well as benefiting from a rich cultural experience, students can draw on large-scale national facilities of both countries and create a worldwide network of contacts across two continents.

The latest set of projects targeted goal #11 from the UN Sustainable Development Goals: Sustainable Cities and Communities.
Falls are a major public health problem [1]. It is the second leading cause of accidental or unintentional injury deaths worldwide. An estimated 646,000 individuals die from falls every year worldwide. Falls are the most common type of injury among older people and a major source of both functional and psychological morbidity. The financial costs from fall-related injuries are huge. The cost of fractures alone caused by falls to the NHS in the UK is staggering and increasing annually (£3.3billion in 2019) in addition to the socio-economic cost that follows [2]. In Taiwan, 1/6 of older people experienced falls in one year, and each spent at least $130,000NTD in the hospital, not including the succeeding care at home.

Although the benefits of exercise for fall prevention have been demonstrated [3], the majority of older people are physically inactive due to several physical and mental limitations they may face. Another alternative treatment such as BCI and motor imagery with providing additional sensory information have the potential enhance movement performance and so decrease the risk of fall [4].
The aim of this project is to explore Brain computer interface and neurofeedback technology as a mechanism to reduce risk of fall in older people.

The suitable applicant will have a
1) BSc (first class or upper second)/MSc/MPhil in Electronics Engineering, Computer Science, Mathematics, Physics or a related subject.
2) Strong theoretical and applied knowledge in signal processing, machine learning, as well as good programming skills in Matlab/C++ or other languages of choice.

It is desirable if the applicant has experience in experimental design, interacting with older people, the application of artificial intelligence in the field, experience in writing academic papers or reports.

Applicants should apply via the University of Liverpool application form, for a PhD in the subject area listed above via: https://www.liverpool.ac.uk/study/postgraduate-research/how-to-apply/

For academic enquires please contact [Email Address Removed].
For enquires on the application process or to find out more about the Dual programme please contact School of Electrical Engineering and Electronics Postgraduate Office ([Email Address Removed])