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Details of Grant 

EPSRC Reference: EP/T021020/1
Title: Quantum Imaging for Monitoring of Wellbeing & Disease in Communities
Principal Investigator: Cooper, Professor J
Other Investigators:
Imran, Professor MA Muckli, Professor LF Murray-Smith, Professor R
Mcintosh, Professor E Gallacher, Dr KIK Faccio, Professor DFA
Vuckovic, Dr A Mair, Professor F Killick, Professor R
Quinn, Dr T
Researcher Co-Investigators:
Project Partners:
Aridhia Intelesant Ltd Moodagent A/S
Department: School of Engineering
Organisation: University of Glasgow
Scheme: Programme Grants
Starts: 01 June 2021 Ends: 31 May 2026 Value (£): 5,625,020
EPSRC Research Topic Classifications:
Instrumentation Eng. & Dev. Med.Instrument.Device& Equip.
Medical Imaging
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:  
Summary on Grant Application Form
We have identified the home as the place where future transformational healthcare changes will occur with the greatest impact potential. Our vision is that the home of the future will be an environment that has the ability to follow our everyday movements, behaviour and wellness. In this sense, it will become an extension of our physical bodies, providing us with feedback, advice and alerts in the presence of anomalies in the data streams collected by new-generation sensors. The analysis of the data-streams from the sensors will be based on clinically approved models, thus effectively bringing highly trained expertise directly to the living environment.

Remote detection and monitoring of parameters such as gait, macro and micro-movements, blood flow, heart rate and potentially even brain function, when combined with data-driven models, will allow to both monitor health and the onset of non-communicable diseases (NCDs) but also recovery from NCDs or surgery with personalised and continuously updated re-habilitation programmes.

This therefore takes the concept of precision medicine and extends it to our overall physical and mental well-being, with the vision of enabling "precision healthcare" delivered to the home.

The sensors we are proposing are based on new-generation quantum-inspired cameras. These cameras can detect extremely low levels of light, thus rendering their presence in the home completely unobtrusive. The cameras can also detect the arrival time of light at the sensor with very high precision and at very high frame rates. The combination of these features enables the measurement of both macro-movement (in a similar fashion to more common cameras) and micro-movement (not currently possible with current, low-cost or low form-factor cameras). Micro-movement detection is sufficiently precise to capture nanometric variations in skin/body shape and thus directly detect blood flow, monitoring the precise shape and variations of heart beat. Future, very ambitious plans, include extending this capability to the brain. Our cameras can also be combined with RF technology to provide richer data, e.g. Doppler signals directly related to speed of movement.

All these indicators will be fed into machine learning models that monitor, learn and are updated over time and, most importantly, adapt to the individuals inhabiting the home environment. Thus, the systems will quickly adapt and evolve for bespoke individuals, providing precision healthcare monitoring and feedback.

Alongside the engineers and computer scientists working on the sensors and data analysis, our programme involves clinicians who will provide the interpretation models for our data and also partners who will give us access to new-generation intelligent homes inhabited by users who are already beta-testing sensors monitoring for example gross movement.

Key Findings
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Potential use in non-academic contexts
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Description This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
Date Materialised
Sectors submitted by the Researcher
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Organisation Website: http://www.gla.ac.uk