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Steady-State Visual Evoked Potential-Based Real-Time BCI for Smart Appliance Control

  • Noel G. Tavares
  • R. S. Gad
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 768)

Abstract

Brain–Computer Interface (BCI) provides an alternative way for humans to communicate with the external environment. BCI systems can be of great help to people with severe motor disabilities who cannot perform normal daily activities. In this paper, we introduce a novel steady-state visual evoked potential (SSVEP)-based brain–computer interface system that control home appliances like electric fan, tube light, etc. Designed system aim is to extract the SSVEP signal and then classify them using PCA. We confirmed the generation of SSVEP frequencies in the online analysis using Fast Fourier Transform. The classification of SSVEP signals is done using Principal Component Analysis.

Keywords

Brain–computer interface (BCI) Steady-state visually evoked potentials (SSVEP) Electroencephalogram (EEG) Fast fourier transform (FFT) Principal component analysis (PCA) 

Notes

Acknowledgements

Authors would like to acknowledge financial assistance from Department of Science and Technology (New Delhi) under Instrument Development Scheme. Author Mr. Noel Tavares would like to thank DST, New Delhi for granting INSPIRE Fellowship to do full time research at Goa University.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of ElectronicsGoa UniversityTaleigao PlateauIndia

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