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A series of publications from 2025–2026.

The Problem with Existing EEG Electrodes

Electroencephalography (EEG) measures the brain’s electrical activity through electrodes placed on the scalp. It is a key tool in neuroscience, clinical diagnosis, and — increasingly — in brain-computer interfaces (BCI) that allow people to control devices with their thoughts.

But there is a practical problem: most EEG systems are designed for clinical settings, not everyday use. Wet electrodes require conductive gel that dries out. Dry metallic electrodes require heavy pressure against the scalp to maintain contact. Both approaches are uncomfortable for long-duration use, which is precisely when BCIs are most valuable.

The SEBS Composite Approach

This research series develops dry EEG electrodes from conductive SEBS (Styrene-Ethylene-Butylene-Styrene) composite materials. SEBS is a thermoplastic elastomer — it is flexible, biocompatible, and processable by standard polymer manufacturing methods including 3D printing. By loading it with conductive fillers (carbon black, metallic particles), we create an electrode material that is soft enough to conform to the scalp without pressure, while maintaining the electrical conductivity needed for EEG signal acquisition.

What We Have Demonstrated

Across a series of papers, this work has established:

  • Formulation and processability: How to select conductive filler type and loading to achieve the target conductivity while maintaining printability and mechanical compliance
  • Electromechanical performance: The electrode’s impedance and signal quality over long wear durations, including under deformation
  • Integrated manufacturing: A method to directly print electrodes onto thermoplastic helmet shells, creating a single-step fabricated EEG headset without manual assembly
  • Validation: Comparison of signal quality against commercial reference electrodes in standard EEG paradigms

This work is carried out in collaboration with Beam Me Up Labs, Prof. Éric David (ÉTS), Prof. Gelareh Momen (UQAC), and Daniel Poirier (Polytechnique Montréal), with support from CREPEC.

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