Fuzzy modeling the influence of temperature on tissue biosensor for measurement of dopamine

The paper treats fuzzy-logic-based modeling the influences of temperature and substrate concentration on the output current of biosensor for measurement of dopamine. Quantitative determination of dopamine in urine and plasma is very important for curing diseases like ganglioneuroma, schizophrenia, manic-depressive psychosis, stress, burn-out syndrome, etc. The measurements made with radioimmunoassay and chromatographically are time consuming processes (over 4 hours) and need expensive laboratory technique. In contrast to them, electrochemical biosensors are very simple, easy to use and cheap devices for measuring of substrates, such as dopamine, etc. A biosensor with active membrane from banana tissue is used for experiments in the paper. Since an enzyme reaction is used for determination of dopamine, temperature strongly influences on the output signal from biosensor. The proposed fuzzy modeling of biosensor input/output dependence (taking into account the temperature influence) is able to cope with small (insufficient) number of experimental data. The high accuracy of the fuzzy approximation is confirmed by simulations in MATLAB environment. The relative errors calculated over new experimental data are used for validation of the proposed method. Additionally, the results are compared with those obtained by ANFIS (adaptive-network-based fuzzy inference system).