The perceiving sensory estimated in an artificial human estimation based sensor system

The authors consider a problem which is basic to perception measurement: to devise an artificial system that mimics the integration of perceptual information into a proposed framework performed by the human sensory system. This paper presents a method for handling complex perceptual information from different sensors that imitate human appreciation and enjoyment of food, in the authors´ case potato chips. They propose a method to measure, analyze and correlate information from a “crush chamber”. Different sensors measure auditory, olfactory and tactile data, then analyze and merge the information into a system opinion. The proposed technique is exemplified by two applications, to estimate aging and to classify different potato chips by collecting, analyzing and fusing sensory quality parameters: crunching, hearing and smelling information. It is shown that by analyzing each single quality parameter, the ailing process of the chips could not clearly be followed. However, fusing multivariate analysis (PCA) of the total sample information the authors are able to follow the aging process. The authors are also able to classify various types of chips