A Cost-Effective 3D-Printed Conductive Phantom for EEG Sensing System Validation: Development, Performance Evaluation, and Comparison with State-of-the-Art Technologies
Abstract
1. Introduction
- Systematic development and validation of a 3D-printed phantom design demonstrating consistent electrical properties suitable for standardized EEG electrode testing, achieving 85% cost reduction and fabrication time reduction from weeks to under 48 h compared to commercial alternatives
- Comprehensive electrical characterization using multi-tier validation: DC resistance measurements (821–1502 ), complex impedance spectroscopy at 100 Hz revealing spatial variation (3.01–6.4 k) and capacitive behavior (phase angles −53° to −67°), and clinical EEG system compatibility demonstration (5–11 k electrode-phantom interface impedance)
- Comparative analysis of six distinct phantom technologies for EEG validation applications, evaluating electrical properties, fabrication requirements, costs, and accessibility limitations to provide evidence-based selection guidance for different research contexts
- Practical demonstration of accessible validation methodologies that enable broader participation in EEG electrode development, particularly benefiting resource-constrained research environments and educational applications
2. State-of-the-Art Analysis: Phantom Technologies for EEG Sensing System Validation
2.1. Commercial Injection-Molded Phantoms
2.2. Saline and Electrolyte Solutions
2.3. Gelatin and Hydrogel-Based Phantoms
2.4. 3D-Printed Conductive Phantoms
2.5. Silicone and Elastomer-Based Phantoms
2.6. Multi-Material Phantoms
2.7. Emerging Textile-Based Phantoms
2.8. Comparative Analysis and Identification of Key Limitations
3. 3D-Printed Conductive Phantom Implementation
3.1. Design and Fabrication Approach
3.1.1. Phantom Architecture and Model Development
3.1.2. Material Selection and Characterization
3.1.3. Manufacturing System Implementation
3.1.4. Process Parameter Optimization
3.1.5. Production Timeline and Resource Requirements
3.2. Electrical Characterization and Validation
3.2.1. Resistance Measurement Protocol
3.2.2. Electrical Performance Results
3.2.3. Signal Transmission and Frequency Response Validation
3.3. Prototype Validation and Quality Control
3.3.1. Scale Model Verification
3.3.2. Multi-Channel EEG System Validation
Experimental Setup and Configuration
Electrode-Phantom Interface Characterization
Spatial Signal Localization
3.3.3. Complex Impedance Spectroscopy Analysis
Regional Impedance Mapping Protocol
Multi-Method Electrical Validation Approach
Complex Impedance Results
Measurement Method Considerations
Complex Impedance Visualization
4. Discussion
4.1. Democratizing Access to EEG Validation Technologies
4.2. Technical Performance and Validation Capabilities
4.3. Strategic Technology Selection Framework
4.4. Economic Impact and Resource Optimization
4.5. Innovation Impact on EEG Sensing System Development
4.6. Future Technological Evolution and Research Directions
4.7. Broader Impact on Biomedical Engineering Education and Research
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Abbreviations
ABS | Acrylonitrile Butadiene Styrene |
CAD | Computer-Aided Design |
CSF | Cerebrospinal Fluid |
CT | Computed Tomography |
ECG | Electrocardiogram |
EEG | Electroencephalography |
FDM | Fused Deposition Modeling |
GelMA | Methacrylate Gelatin |
KCl | Potassium Chloride |
LCR | Inductance, Capacitance, Resistance |
MR | Magnetic Resonance |
MRI | Magnetic Resonance Imaging |
NaCl | Sodium Chloride |
PAA | Polyacrylamide |
PDMS | Polydimethylsiloxane |
PET | Positron Emission Tomography |
PLA | Polylactic Acid |
PVA | Polyvinyl Alcohol |
PVP | Polyvinylpyrrolidone |
RF | Radio Frequency |
TPE | Thermoplastic Elastomer |
TPU | Thermoplastic Polyurethane |
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Phantom Type | Material Cost | Equipment Cost | Production Time | Electrical Properties | Operational Lifespan |
---|---|---|---|---|---|
Injection-Molded [6,10] | £300–500/unit | £5k–20k tooling | Weeks | Consistent, 10–20 cm | Years |
Saline Solutions [17,87] | £10–30 | Minimal | Hours | Adjustable, ionic | Days–weeks |
Gelatin/Hydrogel [34,35] | £30–80 | Minimal | 1–2 days | 2–5 cm, adjustable | Weeks |
3D-Printed [48,52] | £40–150 | 3D printer | 1–3 days | 15–100 cm | Years [55] |
Silicone-based [63,67] | £100–300 | Molds required | 2–3 days | 5–15 cm | Years |
Multi-Material [77] | £200–600+ | Various | 3–7 days | Heterogeneous | Years |
Textile-based [7] | £80–200 | 3D printer + textiles | 2–3 days | 1.8–2.3 k | Years |
Parameter | Conductive Section | Non-Conductive Base |
---|---|---|
Print speed [mm/s] | 75 | 80 |
Printing temperature [°C] | 230 | 225 |
Build plate temperature [°C] | 60 | 60 |
Layer height [mm] | 0.2 | 0.2 |
Line width [mm] | 0.4 | 0.4 |
Infill density [%] | 100 | 20 |
Infill pattern | Zig-zag | Zig-zag |
Wall thickness [mm] | 0.8 | 0.8 |
Support material | White breakaway | White breakaway |
Anatomical Region | Electrode Pair | |Z| (k) | (°) | R (k) | X (k) |
---|---|---|---|---|---|
Frontopolar | Fp1-Fp2 | 3.01 | −59.0 | 1.55 | −2.58 |
Frontal | F3-F4 | 6.40 | −63.9 | 2.83 | −5.74 |
Central | C3-C4 | 3.73 | −60.0 | 1.87 | −3.23 |
Parietal | P3-P4 | 4.86 | −53.4 | 2.89 | −3.91 |
Occipital | O1-O2 | 5.30 | −67.2 | 2.06 | −4.89 |
Temporal | T7-T8 | 4.70 | −62.3 | 2.19 | −4.16 |
Mean ± SD | 4.67 ± 1.36 | −61.0 ± 4.6 | 2.23 ± 0.53 | −4.09 ± 1.19 |
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Akor, P.; Enemali, G.; Muhammad, U.; Crowley, J.; Desmulliez, M.; Larijani, H. A Cost-Effective 3D-Printed Conductive Phantom for EEG Sensing System Validation: Development, Performance Evaluation, and Comparison with State-of-the-Art Technologies. Sensors 2025, 25, 4974. https://doi.org/10.3390/s25164974
Akor P, Enemali G, Muhammad U, Crowley J, Desmulliez M, Larijani H. A Cost-Effective 3D-Printed Conductive Phantom for EEG Sensing System Validation: Development, Performance Evaluation, and Comparison with State-of-the-Art Technologies. Sensors. 2025; 25(16):4974. https://doi.org/10.3390/s25164974
Chicago/Turabian StyleAkor, Peter, Godwin Enemali, Usman Muhammad, Jane Crowley, Marc Desmulliez, and Hadi Larijani. 2025. "A Cost-Effective 3D-Printed Conductive Phantom for EEG Sensing System Validation: Development, Performance Evaluation, and Comparison with State-of-the-Art Technologies" Sensors 25, no. 16: 4974. https://doi.org/10.3390/s25164974
APA StyleAkor, P., Enemali, G., Muhammad, U., Crowley, J., Desmulliez, M., & Larijani, H. (2025). A Cost-Effective 3D-Printed Conductive Phantom for EEG Sensing System Validation: Development, Performance Evaluation, and Comparison with State-of-the-Art Technologies. Sensors, 25(16), 4974. https://doi.org/10.3390/s25164974