Quantum Inspired Imaging for the Early Diagnosis of Disease

The aim of this PhD project is to develop new technologies, concepts and collaborations around quantum sensor technologies and quantum-inspired imaging for the identification/early diagnosis of disease. For example, increased skin temperature, changes in blood distribution/flow, increased heart rate, changes in breathing, micromovements and physical agitation, as well alterations in sleep patterns may be proxies for likely onset of disease.

In one stream of work, the student will also have the opportunity to combine the imaging technologies with AI in order that they can continuously monitor the health of one or more individuals as they move, eat, and sleep. We propose that analysis of these data streams, based upon small but statistically relevant changes in trends in physiological outputs and behaviour will provide proxies providing further evidence for changes in health.

Aims and Objectives: The PhD will focus on the development of relevant detection technologies based on IR-sensing and near-infrared imaging, including time-resolved data (e.g. from SPAD sensors) for the detection of physiological, molecular or mechanical changes "in-body" for individuals in their home environment. The project also has the potential to include:

1. The development of artificial neural network approaches to analyse time-series of data from households, therefore identifying relevant training data sets and time-data traces of changes in physiological proxies for disease with changes in human behaviour;

2. The development of a minimal viable prototype that can be deployed within the household environments. This will involve associated knowledge exchange through engagement with a range of stakeholders including clinicians. For example, it is anticipated that we will collaborate with experts in behavioural sciences/phycology (Professor Lars Muckli) GPs / primary health care scientists (Dr Katie Gallacher and Professor Frances Mair), as well as clinicians (Dr Terry Quinn). We will also have access to beta-test sites and families in a real-world environment, provided by our collaborations with e.g. Howz and Sphere IRC (https://www.irc-sphere.ac.uk), and industries (such as Cisco and Fujitsu). It is anticipated that these stakeholder will provide advice and expertise in product creation, ethics, data protection and public awareness of the technology.

The long-term vision is the development of technologies that can be integrated into networked houses and communities that continuously monitor health, based on the measurement of these small but statistically relevant "markers" as part of connected homes.