Research on Impedance Model of E. coli-NC Membrane Composite Electrode Based on XGBoost Algorithm
Xu Ying 1*, Chen Yangzi1, Liu Zhe1, Sun Lesheng1, Jiang Yang1, Guo Miao2
1(Biomedical Engineering Institute, School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China) 2(School of Information Engineering, Hangzhou Dianzi University, Hangzhou 311305, China)
Abstract：The purpose of this work is to use machine learning method to analyze the concentration of large quantities of E. coli and evaluate the antibacterial effect of low threshold antibiotics. In this paper, XGBoost machine learning algorithm was used to construct a model of E. coli-NC membrane attachment on gold electrodes, which was used to detect the electrochemical impedance spectrum of E. coli at different concentrations. On this basis, the changes of impedance spectrum corresponding to the action of different concentrations of Amikacin Sulfate antibiotics on the standard concentration of E. coli were analyzed. The impedance curves were fitted with ZView to get seven electrochemical parameters according to the Randles equivalent circuit. The main four parameters of Rs,CPE-P, CPE-T and R1, which were extracted by the principal component analysis (PCA) based on the principle of selecting the top 90% of the information quantity, were input to XGBoost prediction model. Prediction models of the two groups of experiments of E. coli liquid concentration and antibiotic concentration were established based on the predicted value of bacterial fluid concentration and antibiotic concentration. The predicted results of both groups were consistent with the experimental results, with the average root mean square error (RMSE) of the predicted E. coli concentration of 2.18×10-3 lg CFU/mL and the maximum difference between the upper and lower limits of the predicted concentration of each group within 1.49×107 CFU/mL. The average RMSE of antibiotics was 7.45×10-3 μL/mL, and the regression accuracy was 0.01 μL/mL, which realized the rapid and accurate prediction of E. coli and antibiotic concentration. Therefore, the impedance model of E. coli-NC membrane based on XGBoost could be applied to quantitatively analyze the mass concentrations of E. coli and the evaluation of the effect of antibiotic antibacterial at critical low threshold, so as to quantitatively evaluate the long-term impedance change caused by the attachment of micro-proteins, bacteria and other biofilms on the electrode surface, showing great application value and significance in the rapid detection of electrochemistry in the field of food safety.
徐莹, 陈扬孜, 刘哲, 孙乐圣, 姜扬, 郭淼. 基于XGBoost方法的大肠杆菌-NC膜复合电极阻抗模型研究[J]. 中国生物医学工程学报, 2021, 40(3): 310-320.
Xu Ying, Chen Yangzi, Liu Zhe, Sun Lesheng, Jiang Yang, Guo Miao. Research on Impedance Model of E. coli-NC Membrane Composite Electrode Based on XGBoost Algorithm. Chinese Journal of Biomedical Engineering, 2021, 40(3): 310-320.
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