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Multi-phase cycle coding for SSVEP based brain-computer interfaces.

Jijun Tong, Danhua Zhu1

  • 1State Key Laboratory of Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital Of Zhejiang University, Hangzhou 310003, China. zdhla@126.com.

Biomedical Engineering Online
|January 18, 2015
PubMed
Summary
This summary is machine-generated.

A new Multi-Phase Cycle Coding (MPCC) protocol enhances brain-computer interfaces (BCIs) using Steady State Visual Evoked Potential (SSVEP). This method increases target options and improves BCI system performance for practical applications.

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Steady State Visual Evoked Potential (SSVEP) based Brain-Computer Interfaces (BCIs) offer rapid response and high Information Transfer Rate (ITR).
  • High stimulation frequencies (30-40 Hz) improve user comfort and mitigate amplitude-frequency issues but limit available stimulation phases.
  • Existing SSVEP BCI protocols face limitations in the number of usable stimulation phases.

Purpose of the Study:

  • To introduce and validate a novel Multi-Phase Cycle Coding (MPCC) protocol for SSVEP-based BCIs.
  • To overcome the limitation of available phases in high-frequency SSVEP stimulation.
  • To enhance the number of encoded targets and overall system performance.

Main Methods:

  • The MPCC protocol codes each target using a block word composed of cyclic codewords.
  • Stimuli involve flickering at a single frequency, combining multiple phases from a defined set.
  • Methods for generating block codes and extracting phases were detailed, followed by experimental validation.

Main Results:

  • Optimal stimulation frequency is subject-specific, with durations exceeding 0.5s yielding better results.
  • The MPCC-based BCI system achieved an average discrimination accuracy of 93.51% ± 5.62%.
  • An Information Transfer Rate (ITR) of 33.77% ± 8.67% was recorded with the MPCC protocol.

Conclusions:

  • The MPCC protocol demonstrates inherent error correction capabilities.
  • MPCC effectively expands the number of encoded targets, thereby improving BCI system performance.
  • The MPCC protocol shows significant promise for the development of practical and efficient BCIs.