Affiliations: [a] Department of CSE, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India
| [b] Department of CSE, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India
| [c] Jain University, Bengaluru, Karnataka, India
Correspondence:
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Corresponding author: G. Nagarajan, Professor, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India. E-mail: [email protected].
Abstract: A brain-computer interface, is a direct communication pathway between a human or animal brain and an external device. Work is being done to identify objects, images, videos and their colour compositions. When humans watch the surrounding environment, visual data is processed by the brain, and it is possible to reconstruct the same on the screen with some appreciable accuracy by analysing the physiological data. This data is acquired by using one of the non-invasive techniques like electroencephalography (EEG) in Brain Computer Interface (BCI). The immediate goal of BCI research is to provide communications capabilities to severely disabled people who are totally paralyzed or ‘locked in’ by neurological neuromuscular disorders, such as amyotrophic lateral sclerosis, brain stem stroke, or spinal cord injury. The prototype discussed in this paper works on features learning and classification centric techniques using support vector machine. The suggested pipeline, ensures successful navigation of a robot in four directions in real time with accuracy of 93%.
