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, we evaluated visual stimuli properties (SPs) for a steady state visually evoked potentials (SSVEP)-based BMI system. We 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. We 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). Our 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. We 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.

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Publication Details

Journal
PLoS ONE
Published
2024-09-17
DOI
https://doi.org/10.1371/journal.pone.0308506
Citations
1
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.34

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article

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

Ercan M. Dede, In-Soo Kim, Muhamed Farooq, Hossein Hamidi Shishavan et al.
1 citations
PLoS ONE
EEG and Brain-Computer Interfaces
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article

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

Ercan M. Dede, In-Soo Kim, Muhamed Farooq, Hossein Hamidi Shishavan, Abhishek Singla, Danny J. Lohan, Kia Golzari, David Zalozhin, Raheli Roy
article en
1 citations

Abstract

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, we evaluated visual stimuli properties (SPs) for a steady state visually evoked potentials (SSVEP)-based BMI system. We 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. We 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). Our 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. We 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.

PLoS ONEVol. 19(9)
Toyota Motor Corporation (Switzerland) (CH), University of Connecticut (US)
Toyota Research Institute, North America
Sustainable cities and communities
Openalex Percentile: Top 41%
EEG and Brain-Computer Interfaces
0.34
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