PROJECT TITLE :

Design Principles and Dynamic Front End Reconfiguration for Low Noise EEG Acquisition With Finger Based Dry Electrodes

ABSTRACT:

Dry electrodes are a convenient various to wet electrodes for electroencephalography (EEG) acquisition systems. Dry electrodes are subject to the next amount of noise at the electrode scalp interface and these effects will be worsened thanks to non-ideal style or improper placement on the head. In this work, we have a tendency to investigate a common dry electrode design primarily based on a range of resistive 'finger’ shaped contacts. We tend to conduct experiments comparing styles with varying numbers of fingers using 2 impedance measurement ways and show that sparser arrangements of fingers are more strong to varying use cases and are a lot of effective at penetrating through hair on the scalp. We then show that these impedance measurement metrics may be used to sort individual fingers within one electrode consistent with quality of electrical contact. We show that the signals from individual fingers will differ from every other significantly thanks to differing native effects of impedance and noise, and demonstrate through experimental results that dynamically choosing only a subset of fingers with sensible contact impedance will improve the overall signal-to-noise ratio of the EEG signal from that electrode.