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Enhancing P300 Detection Using a Band-Selective Filter Bank for a Visual P300 Speller

IRBM, ISSN: 1959-0318, Vol: 44, Issue: 3, Page: 100751
2023
  • 12
    Citations
  • 0
    Usage
  • 14
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    12
    • Citation Indexes
      12
  • Captures
    14
  • Mentions
    1
    • News Mentions
      1
      • 1

Most Recent News

Studies from Antonio Narino University in the Area of Biomedical Engineering Described (Enhancing P300 Detection Using a Band-selective Filter Bank for a Visual P300 Speller)

2023 JUN 05 (NewsRx) -- By a News Reporter-Staff News Editor at Biotech News Daily -- New research on Biotechnology - Biomedical Engineering is the

Article Description

Background: An open challenge of P300-based BCI systems focuses on recognizing ERP signals using a reduced number of trials with enough classification rate. Methods: Three novel methods based on Filter Bank and Canonical Correlation Analysis (CCA) are proposed for the recognition of P300 ERPs using a reduced number of trials. The proposed methods were evaluated with two freely available EEG datasets based on 6x6 speller and were compared with five standard methods: Mean-Amplitude, Step-Wise, Principal Component Analysis, Peak, and CCA. Results: The proposed methods outperform significantly standard algorithms for P300 identification with a maximum AUC of 0.93 and 0.98, and an average of 0.73 and 0.76, using a single trial. Conclusion: Proposed methods based on Filter Bank are robust for the identification of P300 using a reduced number of trials, which could be used in real-time BCI spellers for rehabilitation engineering.

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