Data acquisition, signal processing and modelling: a study of a conducting polypyrrole formate biosensor Part 1: Batch experiment

In this paper a new computerized approach to detection of trace concentrations of formate is considered. In this approach an integrated artificial neural network (ANN) /conducting polymer biosensor is designed. The data collected (current signals) from amperometric detection of the polypyrrole formate biosensor were transferred into a MATLAB™ environment for data and signal processing. Later the data were transferred into an ANN trained computer for modelling and prediction of output. Such an integrated ANN/polypyrrole biosensor system is capable of prediction of formate concentration based on the created models and patterns. The method has advantages of being more selective and more accurate over conventional methods.