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


Citar

Texto integral

Acesso aberto Acesso aberto
Acesso é fechado Acesso está concedido
Acesso é fechado Somente assinantes

Resumo

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.

Sobre autores

N. 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
Rússia, Zelenograd, Moscow; Moscow

P. Rudenko

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

Autor responsável pela correspondência
Email: rudenko.pavel.a@gmail.com
Rússia, Zelenograd, Moscow

V. 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
Rússia, Zelenograd, Moscow; Moscow

K. 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
Rússia, Zelenograd, Moscow; Moscow

E. Litinskaia

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

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

Arquivos suplementares

Arquivos suplementares
Ação
1. JATS XML

Declaração de direitos autorais © Springer Science+Business Media, LLC, part of Springer Nature, 2019