This chapter enlightens the identification of anaemia due to malnutrition
from the colour of the nail images using a smartphone application. This method enables
remote measurements and monitoring using a noninvasive procedure. Since this
method does not involve invasive techniques, there is no blood loss, and it is painless.
In addition, the smartphone application facilitates easy measurements of various
physiological parameters related to the blood. They include Hemoglobin (Hb), iron,
folic acid, and Vitamin B12. This technique can be accomplished using a feed-forward
neural network trained with a Radial Basis Function Network (R.B.F.N.). The image of
the fingernails is photographed using a camera built into the smartphone. Online
anaemia detection smartphone application will classify the anaemic and Vitamin B12
deficiencies as onset, medieval, and chronic stages by feature extraction from the nail
images. The specific measurements made instantly can extract features like the colour
and shape of the fingernails. These features train the R.B.F.N. to identify Anemia due
to malnutrition. This method will enable the depreciation and disposal problems
associated with bio-medical waste. Also, this method will offer a contactless online
measurement scheme. The application could help in the early detection of Anemia due to malnutrition, allowing users to seek medical advice and intervention promptly. In
terms of accessibility, by utilizing a smartphone application, this technology could
reach a broad audience, including those in remote or underserved areas.
Regarding the privacy of medical images, Blockchain's encryption and decentralization
would enhance data privacy and control for users. The data extracted from the nail
images for research is obtained with the user's consent. Anonymized data could be used
for research purposes, contributing to a better understanding of anaemia and
malnutrition trends.
Keywords: Anemia, Image processing algorithms, Nail colour, Radial basis function network.
