Optimization of stimulus properties for SSVEP-based BMI system with a heads-up display to control in-vehicle features

Over the years, the driver-vehicle interface has been improved, but interacting with in-vehicle features can still increase distraction and affect road safety. This study aims to introduce brain-machine interface (BMI)- based solution to potentially enhance road safety. To achieve this goal, the authors evaluated visual stimuli properties (SPs) for a steady state visually evoked potentials (SSVEP)-based BMI system. The authors used a heads-up display (HUD) as the primary screen to present icons for controlling in-vehicle functions such as music, temperature, settings, and navigation. The authors investigated the effect of various SPs on SSVEP detection performance including the duty cycle and signal-to-noise ratio of visual stimuli, the size, color, and frequency of the icons, and array configuration and location. The experiments were conducted with 10 volunteers and the signals were analyzed using the canonical correlation analysis (CCA), filter bank CCA (FBCCA), and power spectral density analysis (PSDA). The authors' experimental results suggest that stimuli with a green color, a duty cycle of 50%, presented at a central location, with a size of 36 cm2 elicit a significantly stronger SSVEP response and enhanced SSVEP detection time. The authors also observed that lower SNR stimuli significantly affect SSVEP detection performance. There was no statistically significant difference observed in SSVEP response between the use of an LCD monitor and a HUD.

• Record URL:
  • http://dx.doi.org/10.1371/journal.pone.0308506
• Supplemental Notes:
  • Copyright: © 2024 Hamidi Shishavan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
• Authors:
  • Hamidi Shishavan, Hossein
  • Roy, Raheli
  • Golzari, Kia
  • Singla, Abhishek
  • Zalozhin, David
  • Lohan, Danny
  • Farooq, Muhamed
  • Dede, Ercan M
  • Kim, Insoo
• Publication Date: 2024

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References;
• Pagination: e0308506
• Serial:
  • PLoS One
  • Volume: 19
  • Issue Number: 9
  • Publisher: Public Library of Science
  • EISSN: 1932-6203
  • Serial URL: https://journals.plos.org/plosone/
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Distraction; Driver vehicle interfaces; Human machine systems; Liquid crystal displays; Machine learning; Optimization
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01934066
• Record Type: Publication
• Files: TRIS
• Created Date: Oct 17 2024 9:15AM