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  Digital Economy & Society: ESRC Wales Doctoral Training Partnership / Health and Care Research Wales PhD Studentship: Understanding and Predicting Falls of People Living with Dementia


   Department of Computer Science

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  Dr A Paiement  No more applications being accepted  Funded PhD Project (European/UK Students Only)

About the Project

Falls are a serious health and social care concern, as they are related to lack of social interaction (going out), hospitalisation, hip fractures, death, immobilisation, etc. There is published evidence that cognitive impairment, especially dementia, is an increased risk factor for falls due to reduced ability to dual-task and share attention. Recent research has focused on developing AI-based methods for detecting falls. However, this research is yet to be set in wider social and psychological contexts.

The project aims at addressing this shortage by combining computer science and psychology methods in a study that seeks to understand the fall mechanisms, and the wider context within which people have falls. This new understanding should allow devising intervention strategies. Key research questions are likely to include:

Can AI-based methods be developed to detect mobility and stability losses, and be deployed in real environments?
What are the environmental factors associated with the detected falls, and that favour attention shift?
Can interventions be designed to alleviate these identified factors?
The successful applicant will design AI-based methods to detect instabilities in gait and posture that are indicative of higher fall risk. These methods will be based on, and extend, the main supervisor’s successful works on identifying movements that deviate from a learnt ‘normal’ model in home environments. They will be used to identify areas in homes that present a higher risk of fall.

Participants aged 65+ with early and middle dementia stages will be recruited, for studies either at home or in care-homes. Focus groups and neuropsychological tests will help link the detected fall-prone areas with the likely causes of increased fall risk, such as causes of attention shifts. Possible interventions to reduce or suppress these elements may be discussed during focus groups as well.

An iterative development strategy will favour user-involvement in the design and evaluation of methods. This will ensure that the developed methods are useable in real scenarios and realise impact. HCRW will help gain direct exposure to Welsh policymakers to help influence policies and enable a maximum impact in Wales.

Eligibility

ESRC studentships are highly competitive. Candidates should have an excellent background in the social sciences, holding a 1st or strong upper 2nd class degree; applications from those also holding a relevant research training Master’s degree (or an equivalent background in research training) will be considered for a ‘+3’ award.

Residential eligibility:

Full awards (fees plus maintenance stipend) are open to UK Nationals and EU students who can satisfy UK residency requirements.

Full-time ESRC studentship award holders cannot hold either a full-time job, or a permanent part-time job, during the period of their award. Part-time ESRC studentship award holders cannot hold a full-time job.

Funding Notes

Studentship awards commence in October 2018 and will cover your tuition fees as well as a maintenance grant (currently £14,553 per annum for 2017/18 for full-time students, updated each year) and includes access to an additional Research Training Support Grant (RTSG). There are other opportunities and benefits available to studentship holders, including an overseas fieldwork allowance (if applicable), internship opportunities, overseas institutional visits and other small grants.

Where will I study?