Pal, Arup Kumar and Roy, Dipanjan and Kumar, G Vinodh and Chatterjee, Bipra and Sharma, L N and Banerjee, Arpan and Gupta, Cota Navin (2019) Empirical Mode Decomposition Algorithms for Classification of Single-Channel Eeg Manifesting Mcgurk Effect. Intelligent Human Computer Interaction.

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Abstract

. Brain state classification using electroencephalography (EEG) finds applications in both clinical and non-clinical contexts, such as detecting sleep states or perceiving illusory effects during multisensory McGurk paradigm, respectively. Existing literature considers recordings of EEG electrodes that cover the entire head. However, for real world applications, wearable devices that encompass just one (or a few) channels are desirable, which make the classification of EEG states even more challenging. With this as background, we applied variants of data driven Empirical Mode Decomposition (EMD) on McGurk EEG, which is an illusory perception of speech when the movement of lips does not match with the audio signal, for classifying whether the perception is affected by the visual cue or not. After applying a common pre-processing pipeline, we explored four EMD based frameworks to extract EEG features, which were classified using Random Forest. Among the four alternatives, the most effective framework decomposes the ensemble average of two classes of EEG into their respective intrinsic mode functions forming the basis on which the trials were projected to obtain features, which on classification resulted in accuracies of 63.66% using single electrode and 75.85% using three electrodes. The frequency band which plays vital role during audio-visual integration was also studied using traditional band pass filters. Of all, the Gamma band was found to be most prominent followed by the alpha and beta bands as in previous studies.

Item Type:	Article
Subjects:	Neurodegenerative Disorders Neuro-Oncological Disorders Neurocognitive Processes Neuronal Development and Regeneration Informatics and Imaging Genetics and Molecular Biology
Depositing User:	Dr. D.D. Lal
Date Deposited:	19 Feb 2020 04:52
Last Modified:	13 Dec 2021 06:25
URI:	http://nbrc.sciencecentral.in/id/eprint/680

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