Toward Non-Invasive Estimation of Blood Glucose Concentration: A Comparative Performance

Toward Non-Invasive Estimation of Blood Glucose Concentration: A Comparative Performance

The present study comprises a comparison of the Mel Frequency Cepstral Coefficients (MFCC), Principal Component Analysis (PCA) and Independent Component Analysis (ICA) as feature extraction methods using ten different regression algorithms (AdaBoost, Bayesian Ridge, Decision Tree, Elastic Net, k-NN,...

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Bibliographic Details
Main Authors: Gustavo A. Alonso-Silverio, Víctor Francisco-García, Iris P. Guzmán-Guzmán, Elías Ventura-Molina, Antonio Alarcón-Paredes
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Mathematics
Subjects:
non-invasive glucose monitoring
medical computing
healthcare
machine learning regression models
Online Access:https://www.mdpi.com/2227-7390/9/20/2529

Internet

https://www.mdpi.com/2227-7390/9/20/2529

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