Iot Based Healing Process For Diabetic Foot Ulcer
Main Article Content
Abstract
This presents an innovative approach to treat diabetic foot ulcers (DFU) by leveraging Internet of Things (IoT) technology. Through a comprehensive data analysis system, DFU progress can be monitored in real time, allowing for timely intervention and improved healing outcomes. The system uses IoT devices to capture images of ulcers, identify the stage of the disease, and provide important insights into the severity of the ulcer. These images are displayed on an LCD screen and sent over the IoT network for analysis. Additionally, the system sends email notifications to healthcare providers to keep them updated on the patient's status and allow them to quickly adjust treatment plans. This continuous monitoring allows healthcare professionals to intervene quickly when needed, improving patient care and reducing strain on healthcare resources. This IoT-based approach represents a significant advance in DFU management, providing personalized treatment plans based on real-time data analysis and enabling better outcomes for patients with diabetic foot ulcers
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Laith Alzubaidi, Mohammed A. Fadhel, Sameer R. Oleiwi, Omran Al-Shamma and Jinglan Zhang, "DFU_QUTNet: diabetic foot ulcer classification using novel deep convolutional neural network".
Manu Goyal, Neil D. Reeves, Satyan Rajbhandari and Moi Hoon Yap, "Robust Methods for Real-time Diabetic Foot Ulcer Detection and Localization on Mobile Devices".
P Shah, R Inturi, D Anne, D Jadhav, V Viswambharan, R Khadilkar, et al., "Wagner’s Classification as a Tool for Treating Diabetic Foot Ulcers: Our Observations at a Suburban Teaching Hospital", Cureus, vol. 14, no. 1, pp. e21501, Jan 2022.
Oliver TI and M. Mutluoglu, "Diabetic Foot Ulcer", In: StatPearls [Internet], Aug 2022.
Kukreja, Gagandeep, Atulya Alok, Anil Reddy and Ruban Nersisson, "IoT Based Foot Neuropathy Analysis and Remote Monitoring of Foot Pressure and Temperature", pp. 1-6, 2020.
Soubache, T. Thirumurugan, B. Annapurna and Singh Raushan, "Diabetic Foot Ulcer Treatment Device Using Peltier and Embedded Electronics", Journal of Physics: Conference Series, vol. 1712, pp. 012041, 2020.
L. Chen, S. Sun, Y. Gao and X. Ran, "Global mortality of diabetic foot ulcer: A systematic review and meta-analysis of observational studies", Diabetes Obesity Metabolism, vol. 25, no. 1, pp. 36-45, 2023.
F. Li, H. Chen, Z. Liu, X. Zhang and Z. Wu, "Fully automated detection of retinal disorders by image-based deep learning", Graefe’s Arch. Clin. Experim. Ophthalmol., vol. 257, no. 3, pp. 495-505, Mar. 2019.
A. Rodríguez-Ruiz, E. Krupinski, J.-J. Mordang, K. Schilling, S. H. Heywang-Köbrunner, I. Sechopoulos, et al., "Detection of breast cancer with mammography: Effect of an artificial intelligence support system", Radiology, vol. 290, no. 2, pp. 305-314, Feb. 2019.
M. H. Yap, B. Cassidy and C. Kendrick, Diabetic Foot Ulcers Grand Challenge, Berlin, Germany:Springer, 2022.
Data-driven digital health technologies in the remote clinical care of diabetic foot ulcers:A scoping review - PMC - NCBI (2023)
A Survey on Impact of Internet of Medical Things Against Diabetic Foot Ulcer | EAI Endorsed Transactions on Pervasive Health and Technology (2021)
"IoT and Cloud Based Healthcare Solution for Diabetic Foot Ulcer" on IEEE Xplore, proposing a plan using IoT to detect ulcers in diabetic patients' feet (2020)
"Preventative Sensor-Based Remote Monitoring of the Diabetic Foot in Clinical Practice" on MDPI, discussing sensor-based remote monitoring to manage diabetic foot ulcers and extend ulcer-free days in remission (2023)
S.P. Pendsey, "Understanding diabetic foot", International journal of diabetes in developing countries, vol. 30, no. 2, pp. 75-79, June 2010