Advanced Polymer Nanocomposite EEG Electrodes for Enhanced Epileptic Seizure Detection: A Comparative Analysis

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Year : 2026 | Volume : 14 | 01 | Page :
    By

    Anmol Chaturvedi,

  • Ashish Raj,

  • Devendra Somwanshi,

  • Reema Ajmera,

  1. Assistant Professor, Department of Electrical and Electronics Engineering, Poornima University, Jaipur, Rajasthan, India
  2. Associate Professor, Department of Electrical and Electronics Engineering, Poornima University, Jaipur, Rajasthan, India
  3. Associate Professor, Department of Electrical and Electronics Engineering, Poornima University, Jaipur, Rajasthan, India
  4. Professor, Department of Computer Science and Engineering, Global Institute of Technology, Jaipur, Rajasthan, India

Abstract

Electroencephalography (EEG) has been very important in the detection of epileptic seizures so as to enable successful diagnosis, surveillance and therapy of epilepsy. Nevertheless, EEG electrodes based on traditional metals may be limited due to high or high contact impedance, lack of biocompatibility, discomfort to patients and prone to motion artifacts, which interfere with signal quality and diagnostic adequacy. The recent progress in material science has resulted in coming up with polymer nanocomposite electrodes that are more promising in electrical, mechanical, and even biocompatible characteristics. The paper will make a comparative analysis of advanced polymer nanocomposite EEG electrodes over the conventional Ag/AgCl electrodes regarding epileptic seizure detection quite exhaustively. The research paper entails the production of flexible polymer nanocomposites electrodes that have conductive fillers namely graphene, carbon nanotubes and silver nanowires. These electrodes are tested in simulated and real practice of EEG collections in environment. The most important performance metrics are contact impedance, signal-to-noise ratio, wearability and patient comfort. EEG signals that have been acquired are then processed by advanced machine learning algorithm to automatically identify seizures to have an end to end study of the effects of electrode materials on the diagnostic value. The measured impedance is substantially lower and signal fidelity much greater for polymer nanocomposite electrodes than it is in metals. Application of machine learning-based classification offers improved accuracy and sensitivity rates, given signals provided by nanocomposite electrodes, which affects their appropriateness in cases of clinical and ambulatory monitoring. Also, user reviews note that the comfort level and comfort during long-term usage were significantly increased, which enables constant tracking.

Keywords: EEG, Epilepsy Detection, Seizure Monitoring, Wearable Sensors, Graphene, Carbon Nanotubes, Silver Nanowires, Contact Impedance, Signal-To-Noise Ratio, Machine Learning.

How to cite this article:
Anmol Chaturvedi, Ashish Raj, Devendra Somwanshi, Reema Ajmera. Advanced Polymer Nanocomposite EEG Electrodes for Enhanced Epileptic Seizure Detection: A Comparative Analysis. Journal of Polymer & Composites. 2026; 14(01):-.
How to cite this URL:
Anmol Chaturvedi, Ashish Raj, Devendra Somwanshi, Reema Ajmera. Advanced Polymer Nanocomposite EEG Electrodes for Enhanced Epileptic Seizure Detection: A Comparative Analysis. Journal of Polymer & Composites. 2026; 14(01):-. Available from: https://journals.stmjournals.com/jopc/article=2026/view=237302


References

  1. Wang, M., G. Mi, D. Shi, N. Bassous, et al. “Nanotechnology and Nanomaterials for Improving Neural Interfaces.” Advanced Functional Materials28, no. 12 (2018). ISSN: 1616-301X.
  2. Dawit, H., Y. Zhao, J. Wang, and R. Pei. “Advances in Conductive Hydrogels for Neural Recording and Stimulation.” Biomaterials Science12 (2024). ISSN: 2047-4830.
  3. Bettucci, O., G. M. Matrone, et al. “Conductive Polymer‐Based Bioelectronic Platforms Toward Sustainable and Biointegrated Devices: A Journey from Skin to Brain Across Human Body Interfaces.” Advanced Materials Technologies7, no. 8 (2022). ISSN: 2365-709X.
  4. Wang, J., T. Wang, H. Liu, K. Wang, K. Moses, et al. “Flexible Electrodes for Brain–Computer Interface System.” Advanced Materials35, no. 15 (2023). ISSN: 0935-9648.
  5. Acar, G., O. Ozturk, A. J. Golparvar, T. A. Elboshra, et al. “Wearable and Flexible Textile Electrodes for Biopotential Signal Monitoring: A Review.” Electronics8, no. 5 (2019). ISSN: 2079-9292.
  6. Mukhopadhyay, S. C., N. K. Suryadevara, and A. Nag. “Wearable Sensors for Healthcare: Fabrication to Application.” Sensors22, no. 13 (2022). ISSN: 1424-8220.
  7. Chen, C., M. Xue, Y. Wen, G. Yao, Y. Cui, et al. “A Ferroelectric Ceramic/Polymer Composite‐Based Capacitive Electrode Array for In Vivo Recordings.” Advanced Materials29, no. 42 (2017). ISSN: 0935-9648.
  8. Manoharan, A. K., M. I. K. Batcha, S. Mahalingam, B. Raj, et al. “Recent Advances in Two-Dimensional Nanomaterials for Healthcare Monitoring.” ACS Nano18, no. 1 (2024). ISSN: 1936-0851.
  9. Li, G. L., J. T. Wu, Y. H. Xia, Q. G. He, et al. “Review of Semi-Dry Electrodes for EEG Recording.” Journal of Neural Engineering17, no. 5 (2020). ISSN: 1741-2560.
  10. He, S., L. Zheng, J. Li, and S. Liu. “Epilepsy Treatment and Diagnosis Enhanced by Current Nanomaterial Innovations: A Comprehensive Review.” Molecular Neurobiology(2025). ISSN: 0893-7648.
  11. Vajravelu, A., M. M. B. Abdul Jamil, M. H. B. Abd Wahab, et al. “Nanocomposite-based Electrode Structures for EEG Signal Acquisition.” Crystals12, no. 1 (2022). ISSN: 2073-4352.
  12. Huang, W., J. Zong, M. Li, T. F. Li, S. Pan, and Z. Xiao. “Challenges and Opportunities: Nanomaterials in Epilepsy Diagnosis.” ACS Nano(2025). ISSN: 1936-0851.
  13. Mohamed, M. El Badry, et al. “A Comprehensive Review of the Recent Developments in the Electroanalytical Methods for the Therapeutic Monitoring of Antiepileptic Drugs.” Critical Reviews in Analytical Chemistry(2024). ISSN: 1040-8347.
  14. Sepasi, T., T. Ghadiri, F. Bani, A. Ebrahimi-Kalan, et al. “Nanotechnology-based Approaches in Diagnosis and Treatment of Epilepsy.” Journal of Nanoparticle Research24 (2022). ISSN: 1388-0764.
  15. Medina, H., and N. Child. “A Review of Developments in Carbon-Based Nanocomposite Electrodes for Noninvasive Electroencephalography.” Sensors25, no. 1 (2025). ISSN: 1424-8220.
  16. Tiwari, S., V. Sharma, M. Mujawar, Y. K. Mishra, and A. Kaushik. “Biosensors for Epilepsy Management: State-of-Art and Future Aspects.” Sensors19, no. 7 (2019). ISSN: 1424-8220.
  17. Yoo, S., M. Kim, C. Choi, D. H. Kim, and S. Hong. “Soft Bioelectronics for Neuroengineering: New Horizons in the Treatment of Brain Tumor and Epilepsy.” Advanced Healthcare Materials(2024). ISSN: 2192-2640.
  18. Ziai, Y., S. S. Zargarian, C. Rinoldi, et al. “Conducting Polymer‐based Nanostructured Materials for Brain–Machine Interfaces.” Wiley Interdisciplinary Reviews: Nanomedicine and Nanobiotechnology(2023). ISSN: 1939-5116.
  19. Gao, X., Y. Bao, Z. Chen, J. Lu, T. Su, and Y. Wei. “Bioelectronic Applications of Intrinsically Conductive Polymers.” Advanced Electronic Materials(2023). ISSN: 2199-160X.
  20. Ramasubramanian, B., V. S. Reddy, V. Chellappan, et al. “Emerging Materials, Wearables, and Diagnostic Advancements in Therapeutic Treatment of Brain Diseases.” Biosensors12, no. 7 (2022). ISSN: 2079-6374.
  21. Aghazadeh, H., M. K. Yazdi, A. Kolahi, M. Yekani, and R. Bagherzadeh. “Synthesis, Characterization and Performance Enhancement of Dry Polyaniline-coated Neuroelectrodes for Electroencephalography Measurement.” Current Applied Physics31 (2021). ISSN: 1567-1739.
  22. Wang, X., Y. Cheng, Z. Qi, J. Zhao, et al. “Bio‐Nano Innovations Targeting the Neurovascular Complex for Epilepsy Treatment.” Advanced Healthcare Materials(2025). ISSN: 2192-2640.
  23. Alahi, M. E. E., M. I. Rizu, F. W. Tina, Z. Huang, A. Nag, and L. Xie. “Recent Advancements in Graphene-based Implantable Electrodes for Neural Recording/Stimulation.” Sensors23, no. 3 (2023). ISSN: 1424-8220.
  24. Lin, S., J. Jiang, K. Huang, L. Li, X. He, P. Du, Y. Wu, J. Liu, and X. Xie. “Advanced Electrode Technologies for Noninvasive Brain–Computer Interfaces.” ACS Nano(2023). ISSN: 1936-0851.
  25. Ali, O. A. M. A., M. F. Shaikh, M. S. Hasnain, et al. “Nanotechnological Advances in the Treatment of Epilepsy.” CNS & Neurological Disorders – Drug Targets(2022). ISSN: 1871-5273.
  26. Alsharif, A. A., N. S. Milan Cucuri, et al. “3D Printed Dry Electrodes for Electrophysiological Signal Monitoring: A Review.” Advanced Materials Technologies(2023). ISSN: 2365-709X.
  27. Li, X., Y. Song, G. Xiao, E. He, J. Xie, Y. Dai, and X. Chen. “PDMS–Parylene Hybrid, Flexible Micro-ECoG Electrode Array for Spatiotemporal Mapping of Epileptic Electrophysiological Activity from Multicortical Brain Regions.” ACS Applied Bio Materials(2021). ISSN: 2576-6422.
  28. Sunwoo, S. H., S. I. Han, H. Joo, G. D. Cha, D. Kim, S. H. Choi, et al. “Advances in Soft Bioelectronics for Brain Research and Clinical Neuroengineering.” Matter(2020). ISSN: 2590-2385.
  29. Gao, S., J. Gong, B. Chen, B. Zhang, F. Luo, and Q. Lin. “Use of Advanced Materials and Artificial Intelligence in Electromyography Signal Detection and Interpretation.” Advanced Intelligent Systems(2022). ISSN: 2640-4567.
  30. Nam, S., C. Park, S. H. Sunwoo, M. Kim, H. Lee, M. Lee, et al. “Soft Conductive Nanocomposites for Recording Biosignals on Skin.” Soft Science(2023). ISSN: 2767-3201.
  31. Zahed, M. A., M. Sharifuzzaman, H. Yoon, et al. “A Nanoporous Carbon‐MXene Heterostructured Nanocomposite‐based Epidermal Patch for Real-time Biopotentials and Sweat Glucose Monitoring.” Advanced Functional Materials(2022). ISSN: 1616-301X.
  32. Guler, E., H. B. Yekeler, Z. N. Ozdemir Kumral, et al. “Fabrication of Oro-Dispersible Sodium Valproate-Loaded Nanofibrous Patches for Immediate Epileptic Innervation.” ACS Biomaterials Science & Engineering(2024). ISSN: 2373-9878.
  33. Chougale, A., S. Vedante, G. Kulkarni, et al. “Recent Progress on Biosensors for the Early Detection of Neurological Disorders.” Electroanalysis(2022). ISSN: 1040-0397.
  34. Zhang, A., A. B. Shyam, A. M. C. Cunningham, et al. “Adhesive Wearable Sensors for Electroencephalography from Hairy Scalp.” Advanced Materials(2023). ISSN: 0935-9648.
  35. Kim, H., E. Kim, C. Choi, and W. H. Yeo. “Advances in Soft and Dry Electrodes for Wearable Health Monitoring Devices.” Micromachines13, no. 4 (2022). ISSN: 2072-666X.
  36. Zhang, S., Y. Song, S. Lv, L. Jing, M. Wang, et al. “Electrode Arrays for Detecting and Modulating Deep Brain Neural Information in Primates: A Review.” Cyborg and Bionic Systems (2025). ISSN: 2097-017X.
  37. Manouchehri, S., B. Bagheri, S. H. Rad, M. N. Nezhad, et al. “Electroactive Bio-epoxy Incorporated Chitosan-Oligoaniline as an Advanced Hydrogel Coating for Neural Interfaces.” Progress in Organic Coatings (2019). ISSN: 0300-9440.
  38. Almeshaal M, Palanisamy S, Murugesan TM, Palaniappan M, Santulli C. Physico-chemical characterization of Grewia Monticola Sond (GMS) fibers for prospective application in biocomposites. Journal of Natural Fibers. 2022 Dec 2;19(17):15276-90.
  39. Palanisamy S, Kalimuthu M, Azeez A, Palaniappan M, Dharmalingam S, Nagarajan R, Santulli C. Wear properties and post-moisture absorption mechanical behavior of kenaf/banana-fiber-reinforced epoxy composites. Fibers. 2022 Apr 2;10(4):32.
  40. Palaniappan M, Palanisamy S, Murugesan TM, Alrasheedi NH, Ataya S, Tadepalli S, Elfar AA. Novel Ficus retusa L. aerial root fiber: a sustainable alternative for synthetic fibres in polymer composites reinforcement. Biomass Conversion and Biorefinery. 2025 Mar;15(5):7585-601.
  41. Palaniappan M, Palanisamy S, Khan R, H. Alrasheedi N, Tadepalli S, Murugesan TM, Santulli C. Synthesis and suitability characterization of microcrystalline cellulose from Citrus x sinensis sweet orange peel fruit waste-based biomass for polymer composite applications. Journal of Polymer Research. 2024 Apr;31(4):105.
  42. Palanisamy S, Kalimuthu M, Palaniappan M, Alavudeen A, Rajini N, Santulli C, Mohammad F, Al-Lohedan H. Characterization of Acacia caesia bark fibers (ACBFs). Journal of Natural Fibers. 2022 Nov 23;19(15):10241-52.
Ahead of Print Subscription Original Research
Volume 14
01
Received 09/07/2025
Accepted 01/09/2025
Published 20/02/2026
Publication Time 226 Days
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