Το έργο με τίτλο Comparison between dry and wet EEG electrodes in an SSVEP-based BCI for robot navigation από τον/τους δημιουργό/ούς Samara Maria, Farmaki Cristina, Zacharioudakis Nikolaos, Pediaditis Matthew, Krana Myrto, Sakkalis, Vangelis διατίθεται με την άδεια Creative Commons Αναφορά Δημιουργού 4.0 Διεθνές
Βιβλιογραφική Αναφορά
M. Samara, C. Farmaki, N. Zacharioudakis, M. Pediaditis, M. Krana and V. Sakkalis, "Comparison between dry and wet EEG electrodes in an SSVEP-based BCI for robot navigation," in Proceedings of the 2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE 2022), Taichung, Taiwan, 2022, pp. 333-338, doi: 10.1109/BIBE55377.2022.00075.
https://doi.org/10.1109/BIBE55377.2022.00075
Electroencephalography-based brain computer interfaces (BCIs) have been widely used in assistive applications for patients suffering from quadriplegia, or even the locked-in syndrome, to promote autonomy and control. Steady-state visual evoked potentials (SSVEPs) is a BCI stimulation protocol that has been employed widely in navigation applications, due to their efficiency and fast response time. In the current study, we use a previously developed SSVEP-based BCI for robotic car navigation with a low-cost EEG recording device, to compare the performance of the easier-to-use dry EEG-electrodes and the commonly-used wet electrodes. We also employ two different stimulus scenarios, a fixed one and an adaptive one optimized for each participant. We tested our system on 23 healthy participants in both an offline session and an online navigation task on a predefined route. The results indicate that our system with the combination of the low-cost EEG device and the dry electrodes achieves comparable performance to the same system using wet electrodes. Moreover, it ensures a more user-friendly and affordable alternative that could be adopted by a larger part of potential users.