Calibration Modeling In Non-Invasive Blood Glucose Levels Using Support Vector Regression

Authors(3) :-Rosni, Hari Wijayanto, Erfiani

Accurate measurement of blood glucose levels is needed in the treatment and prevention of diabetes mellitus. Blood glucose levels can be measured by injuring (invasive) and not injuring (non-invasive) parts of the body. Invasive measurements can cause discomfort for patients and require relatively more expensive costs. One alternative to overcome this problem is to develop a non-invasive measurement tool. The relationship between the two measurement results can be modeled using calibration. The aim of this study was to predict non-invasive blood glucose levels. The data used were part of the data on prototype clinical trial and development research for monitoring tools for non-invasive blood glucose levels at the Bogor Agricultural University (IPB). The approach method used was support vector regression (SVR) for high dimensional data in the calibration model. The results indicated that the SVR using a radial basis function kernel was the best model. Prediction results of non-invasive blood glucose levels had closer blood glucose levels to the results of invasive measurements. This was supported by a greater value of the coefficient of determination and the smaller value of root mean square error prediction. Furthermore, it can be concluded that the model obtained could be used to predict non-invasive glucose levels and could be recommended to related sectors. However, these results were still in a narrow range of data so that it becomes a suggestion for related parties to use more samples in order to widened the range of data.

Authors and Affiliations

Department of Statistics, Bogor Agricultural University, Bogor, West Java, Indonesia
Hari Wijayanto
Department of Statistics, Bogor Agricultural University, Bogor, West Java, Indonesia
Department of Statistics, Bogor Agricultural University, Bogor, West Java, Indonesia

Calibration, Modeling, Non-Invasive Blood Glucose, Support Vector Regression

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Publication Details

Published in : Volume 4 | Issue 11 | November-December 2018
Date of Publication : 2018-12-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 185-189
Manuscript Number : IJSRSET21841123
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Rosni, Hari Wijayanto, Erfiani, " Calibration Modeling In Non-Invasive Blood Glucose Levels Using Support Vector Regression, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 11, pp.185-189, November-December-2018. Available at doi :
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