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Accurate prediction of continuous blood glucose based on support vector regression and differential evolution algorithm

机译：基于支持向量回归和差分演化算法的连续血糖精确预测

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摘要

Type 1 diabetes (T1D) is a chronic disease requiring patients to know their blood glucose values in order to ensure blood glucose levels as close to normal as possible. Hence, the ability to predict blood glucose levels is of a great interest for clinical researchers. In this sense, the literature is rich with several solutions that can predict blood glucose levels. Unfortunately, these methods require the patient to specific their daily activities: meal intake, insulin injection and emotional factors, which can be error prone. To reduce this burden on the patent, this work proposes to use only continuous glucose monitoring (CGM) data to predict blood glucose levels independently of other factors. To support this, support vector regression (SVR) and differential evolution (DE) algorithms were investigated. The proposed method is validated using real CGM data of 12 patients. The obtained average of root mean square error (RMSE) was 9.44,10.78,11.82 and 12.95 mg/dL for prediction horizon (PH) respectively equal to 15, 30, 45 and 60 min. The results of the present study and comparison with some previous works show that the proposed method holds promise. The SVR based on DE algorithm achieved high prediction accuracy while being robustness, automatic, and requiring no human intervention. (C) 2018 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. Published by Elsevier B.V. All rights reserved.
机译：1型糖尿病（T1D）是一种慢性疾病，需要患者知道血糖值，以确保血糖水平尽可能接近正常。因此，预测血糖水平的能力对临床研究人员来说是一个极大的兴趣。从这个意义上讲，文献富含了几种可以预测血糖水平的解决方案。不幸的是，这些方法要求患者特定于他们的日常活动：膳食摄入，胰岛素注射和情绪因素，这可能出错。为了减少该专利的这种负担，这项工作提议仅使用连续葡萄糖监测（CGM）数据来预测其他因素的血糖水平。为了支持这一点，研究了支持向量回归（SVR）和差分演进（DE）算法。使用12名患者的真实CGM数据验证了所提出的方法。对于预测地平线（pH），所获得的均方误差（RMSE）的平均值为9.44,10.78,11.82和12.95mg / dl分别等于15,30,45和60分钟。本研究的结果和与某些先前作品的比较表明，该方法拥有承诺。基于DE算法的SVR实现了高预测精度，同时具有鲁棒性，自动，并且不需要人类干预。 （c）2018年纳雷斯州博士生物庭院研究所和波兰科学院的生物医学工程。 elsevier b.v出版。保留所有权利。

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