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  Towards a method and system for widespread inexpensive unobtrusive continuous measurement and analysis of tremor as one indicator of frailty in an ageing population.


   School of Engineering

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  Prof Ian Underwood  Applications accepted all year round  Funded PhD Project (Students Worldwide)

About the Project

The Advanced Care Research Centre (ACRC) is a new, multi-disciplinary, £20M research centre at the University of Edinburgh. The ACRC will lead society’s response to the grand challenge of an ageing population that is growing in size, longevity and needs through the pursuit of research intended to deliver “high‐quality data‐driven, personalised and affordable care to support the independence, dignity and quality‐of‐life of people living in their own homes and in supported care environments”.

This project sits within the ACRC Academy , a dedicated Centre for Doctoral Training, co-located with the ACRC, whose students will deliver key aspects of the ACRC research agenda through a new doctoral-level research and training programme that will also equip them for careers across a wide range of pioneering and influential leadership roles in the public, private and third sectors.

The PhD with Integrated Study in Advanced Care is a novel, structured, thematic, cohort-based, programme of 48 months duration. Each PhD research project within the Academy has been devised by a supervisory team comprising academic staff from at least two of the three colleges within the University of Edinburgh. Each annual cohort of around twelve will include students with disciplinary backgrounds spanning from engineering and data science to humanities, social science, business and commerce, social work, medicine and related health and care professions. This unique level of diversity is a key attribute of our programme.

Project  

Aim

To develop and benchmark a system that has the potential for unobtrusive continuous measurement tremor using inexpensive, commercially available, ultra-miniature sensors and off-line analysis based on machine learning.  

Objectives

Technology development. Develop the capability to measure limb tremor routinely, continually, unobtrusively and automatically while engaged in day-to-day activities.

Addressing the clinical application. Monitor tremor routinely over the medium to long term in a cohort of normal population in the first instance then elderly patients.

Analysis, data science, clinical diagnosis. Correlate tremor measured by the new system with other measurements of tremor and related indicators.

Description

Tremor is a regular hyperkinetic oscillation of a body part around an axis and is the most common movement disorder of adults. It can be profoundly disabling and an indicator of frailty either independently or in combination with other measures. Whilst all physicians encounter tremor in their practice, accurate and precise quantification of tremor is challenging. In many disorders where tremor is a prominent feature (such as in Parkinson's disease or drug-induced tremor), situational, day-to-day and hour-by-hour fluctuation makes cross-sectional assessment in a clinic appointment potentially misleading, particularly where frailty also creates communication and/or cognitive barriers. Unobtrusive, longitudinal measures of tremor amplitude and frequency would therefore provide valuable information, as tremor can often be treated but medication regime is necessarily patient-specific and involves optimizing medication choice, dose and timing to balance benefit and side-effects. Despite this, there are no widely deployed methods of inexpensively and unobtrusively monitoring tremor and its progression. Led by team that encompasses, engineering, design and clinical practice, this project will explore the development of such a capability.

Eligibility 

We are specifically looking for applicants who will view their cutting-edge PhD research project in the context of the overall vision of the ACRC, who are keen to contribute to tackling a societal grand challenge and who can add unique value to – and derive great benefit from – training in a cohort comprising colleagues with a very diverse range of disciplines and backgrounds. We advise prospective candidates to engage in dialogue with the named project supervisor and/or the Director of the Academy prior to submitting an application. 

Recruitment  

We are running a rolling recruitment process. We will assess applications on a monthly basis, and will continue to do so until our places are filled. The next deadline is 31 March, which will then be moved to 31 April, then 31 May, if places are remaining. 

You must read How to apply prior to application

Please Apply here

Computer Science (8) Medicine (26)

Funding Notes

PhDs are funded with an enhanced stipend for the full 4 year period.
The call is open to candidates of any nationality but funded places for overseas nationals will be strictly limited to 4 international students who can apply for the highly competitive ACRC Global Scholarship.
It is essential to read the How to Apply section of our website before you apply:
https://www.ed.ac.uk/usher/advanced-care-research-centre/academy/how-to-apply
Please apply here:
https://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&edition=2022&id=1048

References

Keywords: Neurology; Movement disorder; Tremor; Frailty; Medical device; Machine Learning

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