Co-Design of Smart and Data-Driven Health Monitoring Furniture for Care Applications

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

Understand and implement co-design practices to optimise smart AI and data driven health monitoring furniture for different care applications.  

Objectives

  • Explore co-design methods/techniques for AI driven integrated sensor system design 
  • Determine the co-design methodology that is suitable for the proposed technology and care 
  • Validation of co-design development methods for initial prototype(s). 
  • Development of prototype(s) using co-design methods for care environment(s) within an interdisciplinary team. 

Description

The project aims to research the development of smart furniture components that could be integrated within different care environments using co-design methodologies. The furniture will have embedded intelligence that comprise intelligent unobtrusive sensors integrated within a data-driven AI platform. 

This research program will develop practical, care-driven, person led technologies that are fit for and co-designed by people in later life/care. In particular, this means exploring and developing techniques to co-design unobtrusive sensor platforms being developed within ACRC and optimizing design and implementation based on the needs of ecologies of end users, care providers, and geriatricians.   

 

Further Information: 

The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity. Please see details here: https://www.ed.ac.uk/equality-diversity

You must read How to apply prior to application

Please Apply here

Closing Date: 

Saturday, April 1, 2023

Principal Supervisor: 

Assistant Supervisor: 

Eligibility: 

Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.

Candidates need to have a good degree in Electronic Engineering or Computer Science. Experience with sensor-based systems and/or implementation of AI based embedded systems is desirable. 

Prospective applicants could also have a good understanding of co-design methodologies, with a special interest in those with experience in incorporating co-design elements in developing technologies. 

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.

Funding: 

Tuition fees + stipend are available for Home/EU and International students

Further information and other funding options.

Informal Enquiries: