A Cost-Effective 3D-Printed Conductive Phantom for EEG Sensing System Validation: Development, Performance Evaluation, and Comparison with State-of-the-Art Technologies

This paper presents the development and validation of a cost-effective 3D-printed conductive phantom for EEG sensing system validation that achieves 85% cost reduction (<i>£</i>48.10 vs. <i>£</i>300-<i>£</i>500) and 48-hour fabrication time while providing consistent electrical properties suitable for standardized electrode testing. The phantom was fabricated using conductive PLA filament in a two-component design with a conductive upper section and a non-conductive base for structural support. Comprehensive validation employed three complementary approaches: DC resistance measurements (821-1502 Ω), complex impedance spectroscopy at 100 Hz across anatomical regions (3.01-6.4 kΩ with capacitive behavior), and 8-channel EEG system testing (5-11 kΩ impedance range). The electrical characterization revealed spatial heterogeneity and consistent electrical properties suitable for comparative electrode evaluation and EEG sensing system validation applications. To establish context, we analyzed six existing phantom technologies including commercial injection-molded phantoms, saline solutions, hydrogels, silicone models, textile-based alternatives, and multi-material implementations. This analysis identifies critical accessibility barriers in current technologies, particularly cost constraints (<i>£</i>5000-20,000 tooling) and extended production timelines that limit widespread adoption. The validated 3D-printed phantom addresses these limitations while providing appropriate electrical properties for standardized EEG electrode testing. The demonstrated compatibility with clinical EEG acquisition systems establishes the phantom's suitability for electrode performance evaluation and multi-channel system validation as a standardized testing platform, ultimately contributing to democratized access to EEG sensing system validation capabilities for broader research communities.