Application of dry EEG electrodes on low-cost SSVEP-based BCI for robot navigationApplication of dry EEG electrodes on low-cost SSVEP-based BCI for robot navigation Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2024-07-292022enElectroencephalography-based brain computer interfaces (BCIs) have been proposed as a promising non-invasive approach for people suffering from neuromuscular disorders to facilitate control and communication with the surrounding environment. Specifically, steady-state visual evoked potentials (SSVEPs) have been successfully used in navigation applications mainly due to their efficiency and quick response time. In this work we present an SSVEP-based BCI for remote robotic car navigation. The robot telepresence is accomplished by sending wirelessly to the user interface the feed of an IP camera that is mounted on the robotic car. This system was developed with the aim to enhance the ease-of-use, employing dry, instead of commonly used wet EEG electrodes, and to reduce the overall cost, using a low-cost open source EEG amplifier. Additionally, we use a robotic car that offers high movement flexibility with precise and fast distance sensors for collision avoidance. We tested our system on 10 participants in both an offline session and in 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 presents comparable performance to a previous system using wet electrodes and a commercial amplifier. Moreover, it ensures a more user-friendly and affordable alternative that could be adopted by a larger part of potential users.Research has been supported by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH CREATE INNOVATE (project code: T1EDK- 01675.)http://creativecommons.org/licenses/by/4.0/2022 IEEE International Conference on Imaging Systems and TechniquesProceedings of the 2022 IEEE International Conference on Imaging Systems and Techniques (IST 2022) Farmaki Cristina Zacharioudakis Nikolaos Ζαχαριουδακης Νικολαος Pediaditis Matthew Krana Myrto Sakkalis, Vangelis Institute of Electrical and Electronics Engineers BCI SSVEP Dry electrodes OpenBCI Robot navigation