Hemodynamic Response Analysis for Mind-Driven Type-writing using a Type 2 Fuzzy Classifier

Laha, Mousumi; Konar, Amit; Rakshit, Pratyusha; Ghosh, Lidia; Chaki, Susmita; Ralescu, Anca; Nagar, Atulya K.

doi:10.1109/fuzz-ieee.2018.8491611

Cited by 4 publications

(3 citation statements)

References 16 publications

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“…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] +…”

Section: Discussionmentioning

confidence: 99%

“…To compare the relative performance of the proposed type-2 fuzzy reasoning with the existing techniques, we employ the metric as the performance index of the proposed algorithm. Table-II provides the results of metric obtained by the proposed type-2 fuzzy set based reasoning techniques against non-fuzzy reasoning algorithms [43]- [45], type-1 [46], and type-2 fuzzy algorithms [47]- [50] are realized and tested for the present perceptual task. This experiment has been performed over 25 healthy subjects and 5 brain-diseased subjects, comprising 10 stimuli, including 6 sessions each, covering 30×3×10×6 = 5400 training instances.…”

Section: A Performance Analysis Of the Proposed Gt2fs Methodsmentioning

confidence: 99%

“…Thirty volunteers, in the age group of 20-45 years, participated in the experiment [38], [39] after maintaining all safety measures according to Helsinki declaration received in 2004 [52]. The participants include 25 healthy subjects with age below 45 years and 5 are suffering from the olfactory disorder.…”

Section: B Participantsmentioning

confidence: 99%

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

2023

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The paper introduced a novel approach for automatic assessment of olfactory perceptualability 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 ) .( n m O 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.

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