Automatic behaviour monitoring through privacy-preserving multimodal data analysis in health and care applications.

The Advanced Care Research Centre (ACRC) is an interdisciplinary, £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 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 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, social work, medicine and related health and care professions. This unique level of interdisciplinarity is a key attribute of our programme. 

Project   

Aim

To research and develop technology for monitoring mental health and well-being status over time, in care settings, through AI-based analysis of multimodal data, with focus on audiovisual data, while addressing privacy issues in the collection and analysis of such data.

Objectives

• To develop audiovisual data collection methods and tools
• To assess the privacy requirements of users
• To develop privacy-preserving automatic affect recognition methods
• To evaluate these methods with respect to performance and privacy preservation. 

Description

Technologies that monitor a person’s mental health by processing behavioural cues extracted from multimodal data, including audio and video, are being intensely researched. These technologies are particularly useful in care settings, for monitoring older individuals to better assess their well-being in a largely non-invasive manner. However, to be truly non-invasive, care technology must protect the user’s privacy. Multimodal signals contain personal information which can threaten the individual’s privacy if improperly handled. This project will address this issue through research and implementation of privacy preserving methods for multimodal data collection, and training and use of machine learning models for healthcare applications.

Eligibility 

Candidates will typically have an undergraduate degree in computer science, electrical engineering, physics, mathematics, or related subjects. Knowledge of and/or interest in signal processing, privacy-based machine learning, mobile application development and affective computing would be desirable. 

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.  

The Academy aims to foster a supportive and collaborative culture, and welcomes candidates with diverse backgrounds and experiences. 

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