Olfactory Perceptual-Ability Assessment by Near-Infrared Spectroscopy using Vertical-Slice based Fuzzy Reasoning

Abstract

The paper introduced a novel approach for automatic assessment of olfactory perceptual-ability of human-subjects using a functional Near Infrared Spectroscopy device. The assessment requires fuzzy functional mapping from spectroscopic measurement to perceptual-ability using Type-2 fuzzy reasoning. The novelty of the work lies in Vertical Slice Based General Type-2 Fuzzy Reasoning which employs fuzzy meet and union between the planes of type-2 measurement and observation spaces using the classical definition of t-norms and s-norms. The results of the meet and the union computation are later used as the Lower and Upper Firing Strength of the fired rule to determine the structure of the inference. Experiments undertaken confirm the efficacy of the proposed technique over traditional functional mapping, involving neural networks, regression analysis, and the like. The proposed technique of olfactory perceptual-ability can be directly employed to determine the thresholds for recognition-probability and discrimination-probability, when submitted to the subject in presence of aromatic noise. An analysis is undertaken to measure the computational overhead, which is found of the order of O(m.n) and run-time complexity of 94.78 ms, where m and n respectively represent discretizations in the vertical slice and features respectively. A statistical test undertaken confirms the superior performance of the proposed system with others at 95% confidence level