Brain Computer Interface and Machine Learning- WIE ILC 2021

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Speaker: Poonam Chaudhary, Assistant Professor, The Northcap University

The dawn of Brain-Computer Interface technology goes back to the decade of 1990s and although it is somewhat novel, in coming years it may considerably transform the solutions implemented by people to connect with computers and other networking infrastructures. This revolutionary technology epitomizes a remarkably developing field of study with its application systems. A characteristic use of Motor Imagery Brain Computer Interface (MI-BCI) is to arrange for a non-muscular and non-conventional channel for communicating with individuals suffering from neuronal disorders. The planning of a precise and consistent MI-BCI structure necessitates the abstraction of useful and easily distinguishable features. The chief point of concern however is that, the makers and designers of BCI instruments emphasize solely on application development, and thus, ignore the security and privacy related issues to a certain extent. Indeed, a mounting number of attacks to BCI applications underscore the presence of such apprehensions. The research paper provides an all-encompassing analysis of the most prominent feature extraction methodologies and classification algorithms in brain-computer interfaces for motor imagery tasks. Current challenges in the purview of security and privacy in brain-computer interface applications are deliberated and conceivable research directions and countermeasures are recommended.

Speaker: Poonam Chaudhary, Assistant Professor, The Northcap University

The dawn of Brain-Computer Interface technology goes back to the decade of 1990s and although it is somewhat novel, in coming years it may considerably transform the solutions implemented by people to connect with computers and other networking infrastructures. This revolutionary technology epitomizes a remarkably developing field of study with its application systems. A characteristic use of Motor Imagery Brain Computer Interface (MI-BCI) is to arrange for a non-muscular and non-conventional channel for communicating with individuals suffering from neuronal disorders...

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