Hemodynamic Response Analysis for Mind-Driven Type-writing using a Type 2 Fuzzy Classifier
| Autor: | Pratyusha Rakshit, Anca L. Ralescu, Mousumi Laha, Atulya K. Nagar, Susmita Chaki, Lidia Ghosh, Amit Konar |
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| Rok vydání: | 2018 |
| Předmět: |
medicine.diagnostic_test
Computer science Speech recognition 02 engineering and technology Electroencephalography 03 medical and health sciences 0302 clinical medicine Frontal lobe Vowel 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing Classifier (UML) 030217 neurology & neurosurgery |
| Zdroj: | FUZZ-IEEE |
| DOI: | 10.1109/fuzz-ieee.2018.8491611 |
| Popis: | We study the vowels detection from brain activation due to vowel sound imageries. At first we experimentally determine the maximum and relatively longer activation that takes place in the frontal or pre frontal lobe during vowel sound Imagination using acquired electroencephalographic signal analysis. Then we capture pre-frontal or frontal vowel sound imagery using a functional near infrared device to extract certain statistical features. Differential evolution based feature selection is used to for dimensionality reduction. The reduced feature set is then used to design an interval type 2 fuzzy classifier to classify the vowels from the pre frontal or frontal f-NIRs response to vowel sound imagination. Experiments undertaken confirm that the proposed classifier outperforms its competitors in classification accuracy for each vowel sound imagery class. They further confirm that the f-NIRs based classification outperforms EEG based modality for better capture of brain activations. Consonants are encoded with two vowel sounds with a space between them. Thus the proposed technique can effectively be used for mind driven type writing of vowels and consonants, serving people suffering from vocal deficiency. |
| Databáze: | OpenAIRE |
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