A Semi-Dry, Visually Comfortable c-VEP BCI with Short Calibration, Conservative Idle-State Behavior, and a VR Proof of Concept
- 1ISAE-SUPAERO
Abstract
Background and Objectives: Code-modulated visual evoked potentials (c-VEPs) provide fast and reliable control signals for reactive brain-computer interfaces (rBCIs). However, deployment beyond laboratories remains limited by visually intrusive stimulation, reliance on wet electroencephalography (EEG), and false activations during non-control periods. We introduce a usability-oriented c-VEP rBCI combining low-salience textured stimulation, slow flashing codes, asynchronous evidence accumulation, and semi-dry EEG acquisition. Methods: Thirty participants evaluated the system on a standard screen using an 11-class keypad typing task. Two identical online typing sessions were separated by a 2-min video-viewing period serving as an explicit idle condition. Feasibility was then assessed in virtual reality (VR) through a proof-of-concept shell-game task involving head movements and immersive rendering constraints. Visual comfort, peripheral distraction, and fatigue were assessed subjectively in both conditions. Results: In the keypad task, the system achieved 99.8% accuracy with 33 s of calibration data and a mean decoding time of 4.3 s. No spurious commands occurred during the tested 2-min idle condition. In VR, online accuracy reached 100%, with a mean decoding time of 5.6 s. Participants reported high visual comfort and minimal peripheral distraction in both conditions, although fatigue was higher in VR. Conclusion: The proposed c-VEP rBCI combines short calibration, high accuracy, comfortable stimulation, semi-dry EEG, and asynchronous decision-making. Performance during the explicit idle condition and VR implementation support the feasibility of wearable and practical c-VEP systems for self-paced interaction beyond laboratory environments. These findings encourage evaluation in longer idle periods and real-world tasks.
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BibTeX
@misc{dehais2026semidry,
title = {{A Semi-Dry, Visually Comfortable c-VEP BCI with Short Calibration, Conservative Idle-State Behavior, and a VR Proof of Concept}},
author = {F. dehais and E. Maggi and K. Cabrera-Castillos},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.29.754884},
url = {https://www.biorxiv.org/content/10.64898/2026.09.29.754884v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - A Semi-Dry, Visually Comfortable c-VEP BCI with Short Calibration, Conservative Idle-State Behavior, and a VR Proof of Concept
AU - F. dehais
AU - E. Maggi
AU - K. Cabrera-Castillos
PY - 2026
DA - 2026/09/29
PB - bioRxiv
DO - 10.64898/2026.09.29.754884
UR - https://www.biorxiv.org/content/10.64898/2026.09.29.754884v1
AB - Background and Objectives: Code-modulated visual evoked potentials (c-VEPs) provide fast and reliable control signals for reactive brain-computer interfaces (rBCIs). However, deployment beyond laboratories remains limited by visually intrusive stimulation, reliance on wet electroencephalography (EEG), and false activations during non-control periods. We introduce a usability-oriented c-VEP rBCI combining low-salience textured stimulation, slow flashing codes, asynchronous evidence accumulation, and semi-dry EEG acquisition. Methods: Thirty participants evaluated the system on a standard screen using an 11-class keypad typing task. Two identical online typing sessions were separated by a 2-min video-viewing period serving as an explicit idle condition. Feasibility was then assessed in virtual reality (VR) through a proof-of-concept shell-game task involving head movements and immersive rendering constraints. Visual comfort, peripheral distraction, and fatigue were assessed subjectively in both conditions. Results: In the keypad task, the system achieved 99.8% accuracy with 33 s of calibration data and a mean decoding time of 4.3 s. No spurious commands occurred during the tested 2-min idle condition. In VR, online accuracy reached 100%, with a mean decoding time of 5.6 s. Participants reported high visual comfort and minimal peripheral distraction in both conditions, although fatigue was higher in VR. Conclusion: The proposed c-VEP rBCI combines short calibration, high accuracy, comfortable stimulation, semi-dry EEG, and asynchronous decision-making. Performance during the explicit idle condition and VR implementation support the feasibility of wearable and practical c-VEP systems for self-paced interaction beyond laboratory environments. These findings encourage evaluation in longer idle periods and real-world tasks.
ER -