Frédéric Dehais

This study develops individualized Gabor flicker stimulation to enhance neural entrainment while improving tolerability during working memory tasks.

This paper introduces a c-VEP brain-computer interface with short calibration, high accuracy, and visual comfort, validated in both standard and virtual reality settings.

This study compares Gabor-based and classical flicker for SSVEP BCIs, finding Gabor flicker more comfortable at low frequencies and plain flicker better at high frequencies, with optimal performance when matched.

This paper uses SSVEP responses to a frequency-tagging flicker to detect attention lapses during prolonged vigilance tasks, finding that SSVEP outperforms other EEG markers.

This paper introduces StAR stimuli for dry EEG Code-VEP BCI, showing improved accuracy and visual comfort compared to traditional flickers.

This study uses periliminal and subliminal flickers to measure spatial attention via SSVEP, showing improved user experience and classification accuracy.

This paper introduces Burst c-VEP, a novel visual stimulus design for BCI that improves classification accuracy and user experience with minimal calibration data.

This paper introduces a dual passive-reactive BCI system for human-machine interaction, demonstrating 100% classification accuracy and 0.94 F1-score in a flight simulator setting.

The paper assesses the feasibility of capturing P300 ERP responses in real-world settings using mobile EEG and eye-tracking during library searches.