An Imperial-led programme to boost the commercialisation of new medical technologies by early career researchers has welcomed its first cohort.
The MedTech SuperConnector is a new entrepreneurial training programme for Early Career Researchers to help them translate their discoveries into new diagnostic tools, medical devices and digital healthcare solutions.
Supported by a £5m grant from Research England, the SuperConnector is an Imperial led consortium involving seven partner institutions: Queen Mary University of London, Bucks New University, The Francis Crick Institute, Royal College of Art, Royal College of Music, Institute of Cancer Research and Royal Veterinary College.
From ground-breaking advances in prosthesis to new clinical applications for machine learning, the programme will provide ten participants with funding, training, mentorship and access to industry partners and patients to help them fast-track the commercialisation of their research.
The MedTech Superconnector forms part of Imperial’s expanding entrepreneurial ecosystem to support staff and students in translating their research into benefits for society. It builds on the College’s Techcelerate programme for postdocs that supported 14 researchers to leave their labs for 3 months earlier this year and pursue their business ideas.
Meet the Imperial participants
Letizia Gionfrida, from the Department of Bioengineering, is developing an all-in-one AI platform that predicts musculoskeletal disorders through machine learning and computer vision.
Letizia says that the NHS spends around £4.6 billion a year on musculoskeletal disorders, in part due to the costly imaging required to diagnose and monitor such conditions. MedK.ai, which is powered by neural networks, allows for remote diagnosis and monitoring of the condition using just a smartphone camera.
This will allow rheumatologists to perform longitudinal investigations with potential tracking of early stage disorders.
George Winfield, who is undertaking an MRes in Medical Device Design & Entrepreneurship, is developing a paper-based breathing monitoring system that uses AI for early detection of patient deterioration from sepsis triggered by an infection.
One of the early symptoms of sepsis is rapid breathing. Currently, breathing rate is measured manually by doctors on observation rounds. Spyras (formerly SpiraSense), which could monitor continuously, would enable doctors to see trends that might not be immediately apparent from manual observations, giving them more information to make an informed decision about patient care.
Ugur Tanriverdi, from the Department of Bioengineering, is creating a soft robotic liner for prosthetics, which uses AI to adapt to limb shape changes. Ro/liner aims to tackle the painful blisters and discomfort caused by ill-fitting prosthetic sockets.
Generally prosthetic sockets are custom made to fit a person’s limb, but due to changes in the muscle tissue, an individual’s limb can change shape over time. This means that the prosthesis will no longer fit correctly, causing it to be uncomfortable. Ugur says that 75% of amputees are unhappy with their prosthetics for this reason, having to change them up to four times a year.
Ro/liner is a robotic liner that fits between the limb and the prosthesis. It is soft enough to provide cushioning, and it uses Artificial Intelligence to adapt to changes in the limb shape by inflating or deflating. Users can also change the cushioning themselves via an app.
Samuel Wilson, from the Department of Mechanical Engineering, has developed a new wearable system for controlling robotic limbs, computers, and other devices using muscle vibration.
Current robotic limbs are usually controlled by electrical systems, which require the use of gel and persistent skin contact, and the signal can often be blocked or interrupted. Samuel says that NU Interface is more comfortable, can perform more functions, and is much simpler to use.
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