Home > Research > Publications & Outputs > Novel technologies for detection and prevention...

Research

Links

Text available via DOI:

View graph of relations

Novel technologies for detection and prevention of diabetic foot ulcers

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter

Published

Standard

Novel technologies for detection and prevention of diabetic foot ulcers. / Reeves, Neil; Cassidy, B; Abbott, Caroline et al.
The Science, Etiology and Mechanobiology of Diabetes and its Complications. Academic Press, 2021. p. 107-122.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter

Harvard

Reeves, N, Cassidy, B, Abbott, C & Yap, MH 2021, Novel technologies for detection and prevention of diabetic foot ulcers. in The Science, Etiology and Mechanobiology of Diabetes and its Complications. Academic Press, pp. 107-122. https://doi.org/10.1016/B978-0-12-821070-3.00007-6

APA

Reeves, N., Cassidy, B., Abbott, C., & Yap, M. H. (2021). Novel technologies for detection and prevention of diabetic foot ulcers. In The Science, Etiology and Mechanobiology of Diabetes and its Complications (pp. 107-122). Academic Press. https://doi.org/10.1016/B978-0-12-821070-3.00007-6

Vancouver

Reeves N, Cassidy B, Abbott C, Yap MH. Novel technologies for detection and prevention of diabetic foot ulcers. In The Science, Etiology and Mechanobiology of Diabetes and its Complications. Academic Press. 2021. p. 107-122 doi: 10.1016/B978-0-12-821070-3.00007-6

Author

Reeves, Neil ; Cassidy, B ; Abbott, Caroline et al. / Novel technologies for detection and prevention of diabetic foot ulcers. The Science, Etiology and Mechanobiology of Diabetes and its Complications. Academic Press, 2021. pp. 107-122

Bibtex

@inbook{81dc2f22f9f4448a8a636bbf8e80bd34,
title = "Novel technologies for detection and prevention of diabetic foot ulcers",
abstract = "Diabetic foot ulcers have a major health and economic cost, frequently leading to hospitalization, amputation, and impacting quality of life. Prevention and early detection of diabetic foot ulcers are key to enabling an improved outlook for this common complication of diabetes. Intelligent insole technology measuring and feeding-back pressure information to the patient on a daily basis has been shown to reduce the incidence of diabetic foot ulcers in high-risk diabetes patients. Timely and frequent pressure “alerts” support offloading adherence. Computer vision techniques involving machine learning can develop models capable of automatically detecting diabetic foot ulcers from foot images. Automatic recognition of foot ulcers improves screening and early detection and is further advanced through developments in cloud computing, which mean that this “artificial intelligence” technology can be employed in any location, not limited by mobile device capabilities. These novel technologies present opportunity for changing the future outlook of diabetic foot care.",
author = "Neil Reeves and B Cassidy and Caroline Abbott and Yap, {Moi Hoon}",
year = "2021",
month = apr,
day = "23",
doi = "10.1016/B978-0-12-821070-3.00007-6",
language = "English",
isbn = "9780128210703",
pages = "107--122",
booktitle = "The Science, Etiology and Mechanobiology of Diabetes and its Complications",
publisher = "Academic Press",

}

RIS

TY - CHAP

T1 - Novel technologies for detection and prevention of diabetic foot ulcers

AU - Reeves, Neil

AU - Cassidy, B

AU - Abbott, Caroline

AU - Yap, Moi Hoon

PY - 2021/4/23

Y1 - 2021/4/23

N2 - Diabetic foot ulcers have a major health and economic cost, frequently leading to hospitalization, amputation, and impacting quality of life. Prevention and early detection of diabetic foot ulcers are key to enabling an improved outlook for this common complication of diabetes. Intelligent insole technology measuring and feeding-back pressure information to the patient on a daily basis has been shown to reduce the incidence of diabetic foot ulcers in high-risk diabetes patients. Timely and frequent pressure “alerts” support offloading adherence. Computer vision techniques involving machine learning can develop models capable of automatically detecting diabetic foot ulcers from foot images. Automatic recognition of foot ulcers improves screening and early detection and is further advanced through developments in cloud computing, which mean that this “artificial intelligence” technology can be employed in any location, not limited by mobile device capabilities. These novel technologies present opportunity for changing the future outlook of diabetic foot care.

AB - Diabetic foot ulcers have a major health and economic cost, frequently leading to hospitalization, amputation, and impacting quality of life. Prevention and early detection of diabetic foot ulcers are key to enabling an improved outlook for this common complication of diabetes. Intelligent insole technology measuring and feeding-back pressure information to the patient on a daily basis has been shown to reduce the incidence of diabetic foot ulcers in high-risk diabetes patients. Timely and frequent pressure “alerts” support offloading adherence. Computer vision techniques involving machine learning can develop models capable of automatically detecting diabetic foot ulcers from foot images. Automatic recognition of foot ulcers improves screening and early detection and is further advanced through developments in cloud computing, which mean that this “artificial intelligence” technology can be employed in any location, not limited by mobile device capabilities. These novel technologies present opportunity for changing the future outlook of diabetic foot care.

U2 - 10.1016/B978-0-12-821070-3.00007-6

DO - 10.1016/B978-0-12-821070-3.00007-6

M3 - Chapter

SN - 9780128210703

SP - 107

EP - 122

BT - The Science, Etiology and Mechanobiology of Diabetes and its Complications

PB - Academic Press

ER -