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dc.contributor.author Tong, A
dc.contributor.author Perera, P
dc.contributor.author Sarsenbayeva, Z
dc.contributor.author McEwan, A
dc.contributor.author De Silva, AC
dc.contributor.author Withana, A
dc.date.accessioned 2023-11-28T05:09:09Z
dc.date.available 2023-11-28T05:09:09Z
dc.date.issued 2023-01
dc.identifier.citation Tong, A., Perera, P., Sarsenbayeva, Z., McEwan, A., De Silva, A. C., & Withana, A. (2023). Fully 3D-Printed Dry EEG Electrodes. Sensors, 23(11), Article 11. https://doi.org/10.3390/s23115175 en_US
dc.identifier.issn 1424-8220 en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/21751
dc.description.abstract Electroencephalography (EEG) is used to detect brain activity by recording electrical signals across various points on the scalp. Recent technological advancement has allowed brain signals to be monitored continuously through the long-term usage of EEG wearables. However, current EEG electrodes are not able to cater to different anatomical features, lifestyles, and personal preferences, suggesting the need for customisable electrodes. Despite previous efforts to create customisable EEG electrodes through 3D printing, additional processing after printing is often needed to achieve the required electrical properties. Although fabricating EEG electrodes entirely through 3D printing with a conductive material would eliminate the need for further processing, fully 3D-printed EEG electrodes have not been seen in previous studies. In this study, we investigate the feasibility of using a low-cost setup and a conductive filament, Multi3D Electrifi, to 3D print EEG electrodes. Our results show that the contact impedance between the printed electrodes and an artificial phantom scalp is under 550 W, with phase change of smaller than 􀀀30 , for all design configurations for frequencies ranging from 20 Hz to 10 kHz. In addition, the difference in contact impedance between electrodes with different numbers of pins is under 200 W for all test frequencies. Through a preliminary functional test that monitored the alpha signals (7–13 Hz) of a participant in eye-open and eyeclosed states, we show that alpha activity can be identified using the printed electrodes. This work demonstrates that fully 3D-printed electrodes have the capability of acquiring relatively high-quality EEG signals. en_US
dc.language.iso en en_US
dc.publisher MDPI en_US
dc.subject EEG en_US
dc.subject 3D printing en_US
dc.subject dry electrodes en_US
dc.subject conductive filament en_US
dc.title Fully 3d-printed dry EEG electrodes en_US
dc.type Article-Full-text en_US
dc.identifier.year 2023 en_US
dc.identifier.journal Sensors en_US
dc.identifier.issue 11 en_US
dc.identifier.volume 23 en_US
dc.identifier.database MDPI en_US
dc.identifier.pgnos 5175 en_US
dc.identifier.doi https://doi.org/10.3390/s23115175 en_US


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