We consider a problem, that is basic to perception measurement: an artificial system that mimics the integration of perceptual information into a proposed framework performed by the human senses. The paper presents a method for optimising complex information from one single sensor that is indirectly based on the human measurement capability, in the mixing process of dough. We propose a method to measure, analyse and correlate sensor information. This technique is exemplified by an industrial application, where the influence of the properties of the human senses on the rheological behaviour of wheat flour dough is estimated and has further been studied in the dynamic mixing process. It is shown that, by dynamic measurements on the mixing machine, the complex behaviour of the mixing process could clearly be followed. However, by implementing human knowledge and experience into the sensor system we manage to adapt a process that works with human preferences. The system＇s ability to optimise various types of bread formulae and different types of wheat flour is also described. An additional benefit is the possibility, by calculations, to predict the behaviour of the wheat flour dough process.