Non-Invasive Hemoglobin Concentration Measurement Using MGGP-Based Model

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Golap:2019:ICAEE,

• author = "Md. Asaf-uddowla Golap and M. M. A. Hashem",
• booktitle = "2019 5th International Conference on Advances in Electrical Engineering (ICAEE)",
• title = "Non-Invasive Hemoglobin Concentration Measurement Using {MGGP}-Based Model",
• year = "2019",
• month = sep,
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/ICAEE48663.2019.8975672",
• ISSN = "2378-2692",
• abstract = "Normally blood sample is collected from human body using needle and after analyzing the sample result is revealed, this type of measurement method is called invasive. On the other hand, in non-invasive method, no blood sample is required only optical data such as photoplethysmogram or non-optical like bio-impedance is enough to measure hemoglobin concentration of blood. Unlike invasive method non-invasive methods are painless, cheap, quicker and easy to carry out. This paper proposes a non-invasive hemoglobin concentration measurement method using PPG characteristic features which is obtained from fingertip video and symbolic regression of multigene genetic programming. In this paper, 39-time domain and 6 frequency-domain features were extracted from PPG signals, additionally gender and age are added to these features. A correlation-based feature selection method was applied to select best features to train and develop a mathematical model. Promising result have been found using the model both for training and testing dataset. The coefficient of determination R2 and MAE obtained by the model are 0.763 and 0.329 respectively which implies that there is a good relation between hemoglobin level and selected features. Hence, the model can be used clinically to estimate hemoglobin concentration level of human blood.",
• notes = "Also known as \cite{8975672}",

}

Genetic Programming entries for Md Asaf-uddowla Golap M M A Hashem

Citations