App launched to help monitor diabetic foot ulcers
An app to help medical professionals detect diabetic foot ulcers and monitor treatment has been developed by a university.
FootSnap captures consistent photographs of the underside of a person’s foot which can be done at any time or place with the use of a tripod and a portable LED spotlight.
Dr Moi Hoon Yap, a senior lecturer in computer science, and Professor Neil Reeves, professor of musculoskeletal biomechanics, from the Manchester Metropolitan University created the app which can be run on an iPad.
Professor Reeves said: “A diabetic foot ulcer is an open wound on the foot and represents a major problem for people with diabetes, being very difficult to heal and in some cases leading on to amputation.
“The app that we have developed at the moment standardises foot photographs.Feet may not necessarily be photographed by clinicians at the moment. If they are, the pictures are not standardised for distance, orientation and lighting as we do with this app.
“The standardisation feature of the app is, however, only the first stage of what we will go onto achieve.We are now incorporating more sophisticated algorithms, which allow for state-of-the-art monitoring and prevention of foot ulceration over time.
“This will be a very useful clinical tool for healthcare professionals to monitor ulcer healing and is a major advantage over the current approach, which is mainly based on subjective judgement.”
A short video to show how to app works has been made and can be watched here.
FootSnap guides medical professionals to orientate and align the person’s foot in such a way as to build up a portfolio of uniform images for comparison.
The app should be available to download in the near future and the developers envisage further evolution of the program will enable it to be used on smartphones and other devices and by less well-trained operators.
Dr Yap said: “FootSnap is a mobile application based on the concept of data-driven research and Internet of Things.
“It was embedded with image processing algorithms to enable standardisation of data capturing. With Lancashire Teaching Hospitals NHS Foundation Trust, we collected a large-scale dataset with ground truth annotation of the ulcers.
“We introduced an end-to-end solution using a deep learning approach for the detection of diabetic foot ulcers with high accuracy.
“In the near future, the optimised light-weight deep learning model will be integrated into FootSnap to enable early prediction of diabetic foot ulcers.”
To test the reliability of FootSnap, Professor Reeves and Dr Yap conducted a successful proof-of-concept study, which was reported in a recent paper published in the Journal of Diabetes Science and Technology.
They compared and analysed how two operators photographed the feet of 15 people with diabetes, aged between 43 and 74, and 15 non-diabetic control volunteers.
The authors concluded: “Standardisation of plantar foot photographs with FootSnap will allow the future implementation of advanced computer vision algorithms with these images, which can be used for monitoring changes in diabetic foot shape, texture, and colour during longitudinal clinical trials or as part of state-of-the-art clinical monitoring procedures.
“This technology may represent the first stage toward a meaningful step forward in the prevention and management of diabetic foot pathologies.”
To read the research, click here.