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Testing of a Short-Term Blood Glucose Prediction Algorithm Using the DirecNet Database


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Abstract

A short-term blood glucose prediction algorithm was validated using the DirecNet clinical database. Noise at 0, 10, 15, 20, and 25% levels was added to blood glucose tracks to assess the stability of the algorithm. Computer modeling showed that the average prediction error was 2.0, 3.0, 6.6, 7.4, and 13.7%, respectively.

About the authors

N. A. Bazaev

Institute of Biomedical Systems, National Research University of Electronic Technology (MIET); Institute for Bionic Technologies and Engineering, I. M. Sechenov First Moscow State Medical University

Email: rudenko.pavel.a@gmail.com
Russian Federation, Zelenograd, Moscow; Moscow

P. A. Rudenko

Institute of Biomedical Systems, National Research University of Electronic Technology (MIET)

Author for correspondence.
Email: rudenko.pavel.a@gmail.com
Russian Federation, Zelenograd, Moscow

V. M. Grinval’d

Institute of Biomedical Systems, National Research University of Electronic Technology (MIET); Institute for Bionic Technologies and Engineering, I. M. Sechenov First Moscow State Medical University

Email: rudenko.pavel.a@gmail.com
Russian Federation, Zelenograd, Moscow; Moscow

K. V. Pozhar

Institute of Biomedical Systems, National Research University of Electronic Technology (MIET); Institute for Bionic Technologies and Engineering, I. M. Sechenov First Moscow State Medical University

Email: rudenko.pavel.a@gmail.com
Russian Federation, Zelenograd, Moscow; Moscow

E. L. Litinskaia

Institute of Biomedical Systems, National Research University of Electronic Technology (MIET)

Email: rudenko.pavel.a@gmail.com
Russian Federation, Zelenograd, Moscow

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