A Comparative Study of Electrical Potential Sensors and Ag/AgCl Electrodes for Characterising Spontaneous and Event Related EEG Signals

For exactly 90 years researchers have used electroencephalography (EEG) as a window into the activities of the brain. Even now its high temporal resolution coupled with relatively low cost compares favourably to other neuroimaging techniques such as magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI). For the majority of this time the standard electrodes used for non-invasive monitoring of electrical activities of the brain have been Ag/AgCl metal electrodes. Although these electrodes provide a reliable method for recording EEG they suffer from noise, such as offset potential drift, and usability issues, for example, difficult skin preparation and cross-coupling of adjacent electrodes. In order to tackle these issues a prototype Electric Potential Sensor (EPS) device based on an auto-zero operational amplifier has been developed and evaluated. The absence of 1/f noise in these devices makes them ideal for use with signal frequencies of ~10 Hz or less. The EPS is a novel active ultrahigh impedance capacitively coupled sensor. The active electrodes are designed to be physically and electrically robust and chemically and biochemically inert. They are electrically insulated (anodized) and scalable. A comprehensive study was undertaken to compare the results of neural signals recorded by the EPS with a standard commercial EEG system. These studies comprised measurements of both free running EEG and Event Related Potentials (ERPs). Results demonstrate that the EPS provides a promising alternative, with many added benefits compared to standard EEG sensors, including reduced setup time, elimination of sensor cross-coupling, lack of a ground electrode and distortion of electrical potentials encountered when using standard gel electrodes. Quantitatively, highly similar signals were observed between the EPS and EEG sensors for both free running and evoked brain activity with cross correlations of higher than 0.9 between the EPS and a standard benchmark EEG system. Future developments of EPS-based neuroimaging include the implementation of a whole head ultra-dense EPS array, and the mapping of distributions of scalp recorded electrical potentials remotely.