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Code-VEP vs. Eye Tracking: A Comparison Study.

Hooman Nezamfar1, Seyed Sadegh Mohseni Salehi2, Matt Higger3

  • 1Cognitive Systems Laboratory, Electrical and Computer Engineering Department, Northeastern University, Boston, MA 02115, USA. nezamfar@ece.neu.edu.

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Summary
This summary is machine-generated.

Brain-computer interfaces (BCI) offer communication for those with paralysis. Comparing electroencephalography-based coded visual evoked potentials (c-VEP) to eye tracking, c-VEP shows greater robustness against movement artifacts.

Keywords:
BCIEEGSSVEPc-VEPeye tracking

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Area of Science:

  • Neuroscience and Biomedical Engineering
  • Assistive Technology Research

Background:

  • Individuals with severe paralysis face communication barriers despite advanced assistive technologies.
  • Brain-Computer Interfaces (BCI) are being developed to restore communication by translating brain signals into speech or commands.
  • Existing BCI modalities include eye gaze tracking and electroencephalography (EEG)-based signals.

Purpose of the Study:

  • To compare the efficacy of coded visual evoked potentials (c-VEP) via EEG against eye gaze tracking as BCI input signals.
  • To evaluate the performance and robustness of these modalities in healthy individuals, identifying potential limitations for specific user groups.

Main Methods:

  • A BCI system was developed and tested using two input modalities: c-VEP derived from EEG and eye gaze tracking.
  • Performance was assessed on healthy participants, focusing on accuracy, sensitivity to movement artifacts, and system reaction time.
  • Participant preferences were recorded, considering factors like system reaction time and robustness.

Main Results:

  • Eye gaze tracking showed variable performance, being ineffective for individuals with corrected vision or unintentional eye squinting.
  • BCI performance using eye tracking was more sensitive to head and body movements compared to c-VEP.
  • Both c-VEP and eye tracking demonstrated similar system reaction times (0.5-1 second for selection).

Conclusions:

  • Coded visual evoked potentials (c-VEP) offer a potentially more robust alternative to eye tracking for BCI applications, especially concerning movement artifacts.
  • While eye tracking is a popular modality, its limitations highlight the need for diverse BCI solutions tailored to individual user needs and physical characteristics.
  • System reaction time and robustness are critical factors influencing user preference and the overall usability of BCI systems.