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Research Article | Open Access |

Comparison of Inter-and Intra-Subject Variability of P300 Spelling Dictionary in EEG Compressed Sensing

Author 1: Monica Fira Author 2: Liviu Goras
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 10 · Published 2016 · Cited by 12

DOI: https://doi.org/10.14569/IJACSA.2016.071049

Abstract

In this paper, we propose a new compression method for electroencephalographic signals based on the concept of compressed sensing (CS) for the P300 detection spelling paradigm. The method uses a universal mega-dictionary which has been found not to be patient-specific. To validate the proposed method, electroencephalography recordings from the competition for Spelling, BCI Competition III Challenge 2005 - Dataset II, have been used. To evaluate the reconstructed signal, both quantitative and qualitative measures were used. For qualitative evaluation, we used the classification rate for the observed character based on P300 detection in the case of the spelling paradigm applied on the reconstructed electroencephalography signals, using the winning scripts (Alain Rakotomamonjy and Vincent Guigue). While for quantitative evaluation, distortion measures between the reconstructed and original signals were used.

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How to Cite this Article

Fira, M., & Goras, L. (2016). Comparison of Inter-and Intra-Subject Variability of P300 Spelling Dictionary in EEG Compressed Sensing. International Journal of Advanced Computer Science and Applications, 7(10). https://doi.org/10.14569/IJACSA.2016.071049

Fira, Monica, and Liviu Goras. "Comparison of Inter-and Intra-Subject Variability of P300 Spelling Dictionary in EEG Compressed Sensing." International Journal of Advanced Computer Science and Applications, vol. 7, no. 10, 2016, https://doi.org/10.14569/IJACSA.2016.071049.

@article{Fira2016,
  title     = {Comparison of Inter-and Intra-Subject Variability of P300 Spelling Dictionary in EEG Compressed Sensing},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {10},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Monica Fira and Liviu Goras},
  doi       = {10.14569/IJACSA.2016.071049},
  url       = {https://doi.org/10.14569/IJACSA.2016.071049}
}

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