EPSRC has announced details of 20 healthcare technologies projects which have been awarded, funded with an investment of £30.8 million. Four projects were co-funded with the Medical Research Council (MRC). Manchester lead a Sandpit award (Andy Weightman £400k), a Healthcare Impact Partnership award (Goran Nenadic £750k) and a Network Plus award (Peter Gardner £800k), and we have involvement in a further Sandpit award led by Heriot-Watt.

Manchester led Sandpit award: HappierFeet – Disrupting the vicious cycle of healthcare decline in Diabetic Foot Ulceration through active prevention: The future of self-managed care

Led by: Dr Andrew Weightman, The University of Manchester.

Co-funded by the Medical Research Council (MRC). £400,000.

Diabetic foot ulcers affect a quarter of people with diabetes, costing the NHS £1 billion annually. A team led by Dr Andrew Weightman at The University of Manchester aims to address the issue by co-designing, with patients, the self-managed use of smart shoe insoles. These are intended to identify early signs of ulceration through the use of pressure, temperature, inertial measurement units and acoustic sensors. Using actuators that convert energy into movement, they will adjust the way people walk to support safe and comfortable movement. This will encourage people prone to diabetic foot ulcers to be more active while managing their conditions securely. Dr Weightman will collaborate with Andrew Eccles (The University of Strathclyde), Dr Katherine Bradbury (The University of Southampton), Prof Helen Dawes (Oxford Brookes University) and Dr Safak Dogan (Loughborough University) on the project. This multidisciplinary approach to developing a digital healthcare solution is supported by a £400,000 grant through the research sandpits call funded by EPSRC and MRC.

Healthcare Impact Partnership award: ‘Integrating hospital outpatient letters into the healthcare data space’

Led by: Professor Goran Nenadic, The University of Manchester

EPSRC support: £750,000

This project will use Natural Language Processing (NLP) and text mining to unlock information stored in outpatient letters and link it with other health data.

Researchers aim to develop new methods to extract key clinical events from letters and represent their details in a computerised form so they can be easily accessed. In doing so, they will ensure the information in the outpatient letters can be linked to other hospital databases while ensuring data protection.

Researchers will demonstrate the potential impact of the new system through two case studies with clinical and business partners.

The first case study will demonstrate how the proposed models can assist in timely, efficient, dynamic and transparent identification of patients for shielding in a pandemic, or for vaccination prioritisation.

The second case study will illustrate how the same information can be used address important gaps in our knowledge about health and care, including disease prevalence and drug utilisation patterns.

All outputs will be developed in a way that can be scaled beyond the single clinical site and single speciality.

Network Plus award: Integrating Clinical Infrared and Raman Spectroscopy with digital pathology and AI: CLIRPath-AI

Led by: Professor Peter Gardner, The University of Manchester

EPSRC support: £800,000

Biopsy information is a key feature of disease diagnosis. This involves the removal and examination of a small sample of tissue from a patient.

Inspection of the sample, coupled with other relevant information, is the basis on which a diagnosis is generally made. This process is not ideal, however, as is not exact and depends upon the opinion of the clinicians, which may differ.

Recently, AI has been used to examine high-resolution photographs of biopsy slides to help the pathologists make diagnoses.

However, analysing the data from just the visible region of the spectrum severely restricts information content of the images obtained. Using other techniques outside the visible spectrum, such as infrared and Raman, can help distinguish diseased from non-diseased cells.

This funding will support a network of partners across digital pathology and AI that will develop dynamic and synergistic interaction between these separate communities.

Sandpit award led by Heriot-Watt University – Digital Health: On-organ Sensing For Bowel Monitoring – A Bottom Up Approach

Led by: Dr Michael Crichton, Heriot-Watt University, involving Dr Alex Casson, The University of Manchester

Co-funded by the Medical Research Council (MRC). £400,000.

Researchers aim to develop a bowel sensor that could alert people when they need to go to the toilet through a smart phone app.

This could be used to help the estimated 1.5% of the UK population who suffer from faecal incontinence, allowing them to manage the condition and lead more active, confident lives.

These discreet digital sensors would sit in the large intestine and track the movement of stools, acting as an early warning system.

The project also involves researchers at The University of Manchester, University of Stirling, Sheffield Hallam University and The Glasgow School of Art.