Dry EEG-electrodes

1 minute read

Summary
Date 2021-2025
Tags composites, 3d-printing, thermoplastics, electrodes, EEG
Partners Beam Me Up Augmented Intelligence, Prof. Éric David, Daniel Poirier eng., Prof. Gelareh Momen
Recruiting 1MEng, 1 PhD

We are currently recruiting a PhD student to work on this subject. Contact me if you are interested.

This project is supported and financed by the CREPEC.

Today, several types of electrodes are used in electroencephalography (EEG). Although these electrodes have undergone various improvements to increase their performance, comfort and accuracy, the most efficient models are made of metallic materials that are assembled on a “frame” often made of thermoplastic that allows the electrodes to be approximately positioned on the individual’s skull. However, one of the main drawbacks of these electrodes is that they require a lot of pressure or even, for some, superficial abrasion of the upper skin layer of the skull with a pointed shape, which makes them uncomfortable and very difficult to use for long periods of time, especially because of the metallic materials used.

The top image shows an example of two commercial systems sold by Bitbrain. The bottom image presents the difference between wet and dry electrodes (Bibtrain).

Beam Me Up Labs has been working for the past five years to develop tools that use artificial intelligence to perform EEG signal analysis and classification. However, potential applications of this work now require the ability to collect data using EEG electrodes for periods of several hours while operators perform various activities. This project proposes the development of a dry EEG electrode architecture made of conductive composite materials to allow consistent signal acquisition for long durations for active users. It is also proposed to develop a manufacturing method to directly fabricate these electrodes on a helmet made of thermoplastic or composite materials to provide an integrated manufacturing process.

To do so, we are currently hiring a PhD student in Mechcanical Engineering. Follow the instruction provided here if you’d like to apply.

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