Brain Computing Interface using Deep Learning for Blind People
V. J. Chakravarthy1, M. Seenivasan2
1V. J. Chakravarthy, P.G. Department of ComputerScience, The New College, Chennai.
2M. Seenivasan, Department of mathematics, Annamalai university, Annamalai Nagar, Tamilnadu, India.
Manuscript received on November 12, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on 30 November, 2019. | PP: 8227-8230 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8906118419/2019©BEIESP | DOI: 10.35940/ijrte.D8906.118419
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© 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 developing area of research in Brain Computer Interface (BCI) is used to enhance the quality of human computer applications. It can be decoding individuals by the computer device signals converted into commands between human’s neural world and outer physical world. The brain use bodies under some circumstances to interact with the external world and also brain can be depressed of their sensing abilities namely blindness or deafness. In this study, analyze of brain’s behavior using BCI for blind people in spatial activity. The common beliefs in blind people using other senses by compensate their lack of vision. In case of BCI system can able to understand the brain’s activity even in very difficult challenge. Therefore we propose the data mining technique. In this research work, deep learning approach based on the framework of Convolution Neural Networks (CNN) with Long Short-Term Memory (LSTM) can help us to discover their brain’s activity for blind people.
Keywords: Brain-computer interface (BCI), blind people, Convolution Neural Networks (CNN), deep learning, Long Short-Term Memory (LSTM)..
Scope of the Article: Deep Learning.