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Comparison between dry and wet EEG electrodes in an SSVEP-based BCI for robot navigation

Samara Maria, Farmaki Cristina, Zacharioudakis Nikolaos, Pediaditis Matthew, Krana Myrto, Sakkalis, Vangelis

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URI: http://purl.tuc.gr/dl/dias/2AB35C19-AAFB-4DEF-91ED-EB6396E764B0
Year 2022
Type of Item Conference Full Paper
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Bibliographic Citation 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
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Summary

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.

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