Abstract
Brain–computer interface (BCI) is a method of communication between the brain and computer or machines, which use the neural activity of the brain. This neural activity communication does not occur using the peripheral nervous system and muscles, as is the usual case in human beings, but through any other mechanism. This paper focuses on different types of feature extraction techniques to explore a new kind of BCI paradigm and validate whether it can give a better ITR as compared to the existing paradigms.
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Acknowledgements
We would like to thank Axxonet solutions pvt limited for their immense support in getting the data for our work. They helped in providing the BESS software and the supporting hardware for data extraction from the human brain.
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Anupama, H.S., Jain, R.V., Venkatesh, R., Mahadevan, R., Cauvery, N.K., Lingaraju, G.M. (2018). Implementing and Analyzing Different Feature Extraction Techniques Using EEG-Based BCI. In: Sa, P., Bakshi, S., Hatzilygeroudis, I., Sahoo, M. (eds) Recent Findings in Intelligent Computing Techniques . Advances in Intelligent Systems and Computing, vol 708. Springer, Singapore. https://doi.org/10.1007/978-981-10-8636-6_39
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DOI: https://doi.org/10.1007/978-981-10-8636-6_39
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