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Experimental Recording and Computational Analysis of EEG signals for a Squeeze Task: Assessments and Impacts for Applications

Publication Type : Conference Paper

Thematic Areas : Learning-Technologies, Medical Sciences, Biotech

Publisher : IEEE

Source : Proceedings of the Seventh International Conference on Advances in Computing, Communications and Informatics (ICACCI-2018), Bangalore, Karnataka, India

Url : https://ieeexplore.ieee.org/document/8554913

Keywords : Electroencephalography, human motor execution, Signal analysis, squeeze task

Campus : Amritapuri

School : School of Computing, School of Biotechnology

Center : Computational Bioscience, Amrita Mind Brain Center, Biotechnology, Computational Neuroscience and Neurophysiology

Department : Computer Science, Computational Neuroscience Laboratory, biotechnology

Year : 2018

Abstract : Localization of neural activities from electroencephalography measurements and attributing a motor task to its neural signature is becoming a trend in neuroscience and brain computer interface research. For elucidating brain functions in healthy subjects and motor dysfunctions patients, a motor-related squeeze task, a simple daily task was employed in this study. Using low-cost electroencephalography devices in mapping human brain for understanding neural microcircuitry roles during a squeeze task as a biomarker for brain function was the objective. EEG data was recorded from eight healthy right-handed volunteers (4 female and 4 male) of different age group, performing squeeze task on a rubber ball applying graded forces. Using time and frequency domain analysis, we show frontal asymmetry attributed to activity from electrodes in AF3, AF4, F3, F4, F7 and F8 role-specific regions for identifying motor planning and motor execution characterized by predominant mu and beta oscillations.

Cite this Research Publication : Krishnan M, Edison L, Radhamani R., Nijin Nizar, Dhanush Kumar, Manjusha Nair, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “Experimental Recording and Computational Analysis of EEG signals for a Squeeze Task: Assessments and Impacts for Applications”, in Proceedings of the Seventh International Conference on Advances in Computing, Communications and Informatics (ICACCI-2018), Bangalore, Karnataka, India

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