Open AccessPRE-DETECTION OF FOOT ULCER FOR DIABETIC PATIENT USING THERMAL IMAGER
Author(s) -
V. Abinaya Priya,
D. Pamela,
K. Geard Joe Nigel,
Prawin Angel Michael
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1937/1/012032
Subject(s) - diabetic foot ulcer , foot (prosody) , medicine , histogram , diabetes mellitus , diabetic foot , population , physical medicine and rehabilitation , surgery , artificial intelligence , computer science , image (mathematics) , linguistics , philosophy , environmental health , endocrinology
As per the statistics taken in the year 2020, a measurable audit shows that over 35% of the Indian population is influenced with foot ulcer. Foot ulcer is an issue looked by the greater part of the patient who have gone through diabetes mellitus (DM). Around 20% of the diabetes patients is influenced by foot ulcer, another 20% is affected by diabetic neuropathy, 30% patient are influenced with both the conditions. Generally the foot ulcer can be inspected with x-beams, bone output, MRI, CT, Bacterial culture of the ulcer, and even with blood tests. These methods are inspected by obtrusive method of estimations that will hurt the patient more. In order to reduce the discomfort during the interaction and furthermore for the early identification of this condition, this arrangement has been created. This pre-recognition measure is a non-intrusive method for estimation with the thermal imager. The temperature scope of ordinary foot is under 30 degree Celsius. It very well may be fluctuated (expanded) least of 2 degree Celsius for ulcered foot. These ulcered foot pictures has been procured with the assistance of thermal imager (AMG8833) and handled utilizing MATLAB and result is shown in a histogram. This histogram helps us to differentiate the typical and ulcered foot. The classification is done using neural network.