A Computational Intelligence Paradigm with Human Computer Interface Learning
Kiran J Waghmare1, Reeja S R2

1Kiran Waghmare, Assistant Professor, Department of Computer Engineering, Don Bosco College of Engineering, (Goa), India.

2Dr. Reeja S R, Ph.D, Visvesvaraya Technological University, RNSIT Bangalore (Karnataka), India.

Manuscript received on 05 December 2019 | Revised Manuscript received on 13 December 2019 | Manuscript Published on 31 December 2019 | PP: 384-389 | Volume-9 Issue-2S December 2019 | Retrieval Number: B10321292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1032.1292S19

Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The cognitive Science is the leading technology which works on the principle of Neuroscience. Human Computer Interface is a challenging approach in neurosciences, which is the leading method to handle the brain activities to control external communications with the electronic devices for physically challenged human beings. The various HCI applications are developed with this advance technology. This helps in various patients which are physically challenged or facing the lock in syndrome, a condition where limbs are not functioning to full extent. Therefore, this paper is the review paper to the various EEG signal classification techniques using different taxonomy with techniques like linear, nonlinear, stable-ubstable, static-discriminant to design various HCI applications.

Keywords: Human Computer Interface; Learning; Brain Activity; Signal Pattern; Classification.
Scope of the Article: Computer Vision