Hemodynamic Analysis for Olfactory Perceptual Degradation Assessment Using Generalized Type-2 Fuzzy Regression

Abstract

Olfactory perceptual degradation refers to the inability of people to recognize the variation in concentration levels of olfactory stimuli. The paper attempts to assess the degree of olfactory perceptual degradation of subjects from their hemodynamic response to olfactory stimuli. This is done in 2 phases. In the first (training) phase, a regression model is developed to assess the degree of concentration levels of an olfactory stimulus by a subject from her hemodynamic response to the stimulus. In the second (test) phase, the model is employed to predict the possible concentration level experienced by the subject in [0, 100] scale. The difference between the modelpredicted response and the oral response (the center value of the qualitative grades) of the subject about her perceived concentration level is regarded as the quantitative measure of the degree of subject's olfactory degradation. The novelty of the present research lies in the design of a General Type-2 fuzzy regression model, which is capable of handling uncertainty due to the presence of intra-and inter-session variations in the brain responses to olfactory stimuli. The attractive feature of the paper lies in adaptive tuning of secondary membership functions to reduce model prediction error in an evolutionary optimization setting. The effect of such adaptation in secondary measures is utilized to adjust the corresponding primary memberships in order to reduce the uncertainty involved in the regression process. The proposed regression model has good prediction accuracy and high time-efficiency as evident from average percentage success rate (PSR) and run-time complexity analysis respectively. The Friedman test undertaken also confirms the superior performance of the proposed technique with other competitive techniques at 95% confidence level.

Olfactory Perceptual-Ability Assessment by Near-Infrared Spectroscopy Using Vertical-Slice Based Fuzzy Reasoning

“…It would also serve as a tool for the selection of tea-tasters based on their measure of olfactory perceptual-ability from brain-response to olfactory stimuli. Algorithm Type-I Fuzzy sets based reasoning [46] + IT2FS based reasoning [47] + GT2FS based reasoning [48] + SA-GT2FGG [49] based reasoning + Semi-GT2FS based reasoning [50] + Vertical slice GT2FS based reasoning [35] +…”

“… the secondary plane. For construction of , ~j B the concentration grade of the odor stimulus obtained from the oral response of the subject is evaluated from each session comprising 5 trials, and thus for 6 sessions in a day, six measures of concentration grades are available [35]. A Gaussian type-1 MF is constructed with mean and variance respectively as the mean and variance of six oral responses.…”

“…Formula (31) provides an estimate of perceptual-ability C with a minimum value alpha, assuming that the concentration of the aromatic impurity is less than a threshold .  (33) where (34) In case and are independent, the composite probability: (35) holds. This formula provides the basis of perceptual-ability with a minimum value assuming that of the aromatic substance is limited to and impurity of the aromatic noise…”

“…5(a). The fNIRs device contains 8 infrared (IR) sources and 8 infrared detectors to acquire the brain response of a subject during olfactory stimulation [35] channels are utilized for data acquisition, followed by nearest neighboring source-detector combinations according to 10-10 optode placement strategy. Fig.…”