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Cost-efficient and Custom Electrode-holder Assembly Infrastructure for EEG Recordings.
Yuan-Pin Lin1, Ting-Yu Chen2, Wei-Jen Chen3,4
1Laboratory for Neuroergonomics, Institute of Medical Science and Technology, National Sun Yat-sen University, Kaohsiung 80424, Taiwan. yplin@mail.nsysu.edu.tw.
This study introduces a customizable, 3D-printed EEG electrode holder for adaptable brain-computer interface (BCI) research. The cost-efficient design allows personalized electrode placement for improved brain activity signal quality.
Area of Science:
- Neuroscience and Biomedical Engineering
- Focus on electroencephalography (EEG) and brain-computer interfaces (BCI).
Background:
- Mobile EEG technologies enable real-world brain activity monitoring.
- Existing EEG headsets have fixed designs, limiting adaptability and generalizability for BCI studies.
- A need exists for flexible and cost-effective EEG hardware solutions.
Purpose of the Study:
- To design and demonstrate a custom, cost-efficient EEG electrode holder infrastructure.
- To enable adaptable electrode montage and head size fitting for improved signal quality.
- To validate the practical application of the holder in capturing neurophysiological signals.
Main Methods:
- Designed a modular EEG electrode holder using a sensor-positioning ring, inter-ring bridge, and bridge shield.
- Fabricated the holder using a low-cost fused deposition modeling (FDM) 3D printer.
- Tested the holder's performance in capturing event-related potentials (ERP) and steady-state visual-evoked potentials (SSVEP) in 15 subjects.
Main Results:
- The custom holder was easily fabricated using an FDM 3D printer.
- The holder allowed for user-defined electrode placement and adaptation to individual head sizes.
- Demonstrated successful capture of ERP and SSVEP signatures, indicating practical utility.
- Achieved optimal electrode-scalp contact and signal quality.
Conclusions:
- A cost-efficient, customizable EEG electrode holder infrastructure was successfully developed.
- The design offers a flexible and adaptable solution for fundamental EEG studies and BCI applications.
- This approach facilitates personalized neuroelectrical brain activity monitoring and research.
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