Non-Invasive Anemia Detection Tool with Application of Mini Spectrometry Base Machine Learning

Theresia Laura da Costa, Elsa Alfiatun, Risa Kusuma, Sari Wulandari

2023

Abstract

Anemia is a condition in which the level of hemoglobin (Hb) in the body is reduced. Prolonged anemia can cause heart problems, pregnancy disorders, and even death. According to the 2018 basic health research data, anemia sufferers in Indonesia have increased to 48.9%. to reduce the level of anemia, early detection is needed, but the existing tools are usually invasive, namely using blood samples, which certainly reduces public interest. This study aims to make an efficient non-invasive anemia detection tool as an option in anemia detection. This tool was developed using the working principle of mini spectrometry, which recognizes light sources in mini spectrometry using Near-infrared because the Hb wavelength is within the near-infrared wavelength range. The Hb wavelength is 1700-1725 nm and the near-infrared wavelength is 1000-2500 nm. The Photo-NIR detector is used as a sensor because it can capture signals according to the near-infrared wavelength. The method used in signal processing is the Principal Component Analysis (PCA) method for feature extraction and two feature variations are produced. Furthermore, grouping was carried out using the Fuzzy C Means (FCM) method so as to produce anemic and non-anemic data based on the degree of membership. The results of this study obtained an accuracy of 88%. In conclusion, the non-invasive detection tool succeeded in separating anemic and non-anemic samples. Therefore, a non-invasive detection tool is needed as an option for the detection of anemia.

Paper Citation

in Harvard Style

Laura da Costa T., Alfiatun E., Kusuma R. and Wulandari S. (2023). Non-Invasive Anemia Detection Tool with Application of Mini Spectrometry Base Machine Learning. In Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD; ISBN 978-989-758-678-1, SciTePress, pages 38-45. DOI: 10.5220/0012441400003848

in Bibtex Style

@conference{icaisd23,
author={Theresia Laura da Costa and Elsa Alfiatun and Risa Kusuma and Sari Wulandari},
title={Non-Invasive Anemia Detection Tool with Application of Mini Spectrometry Base Machine Learning},
booktitle={Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD},
year={2023},
pages={38-45},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012441400003848},
isbn={978-989-758-678-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Advanced Information Scientific Development - Volume 1: ICAISD
TI - Non-Invasive Anemia Detection Tool with Application of Mini Spectrometry Base Machine Learning
SN - 978-989-758-678-1
AU - Laura da Costa T.
AU - Alfiatun E.
AU - Kusuma R.
AU - Wulandari S.
PY - 2023
SP - 38
EP - 45
DO - 10.5220/0012441400003848
PB - SciTePress