Practical sensing of biopotentials such as the electroencephalogram (EEG) in operational settings has been severely limited by the need for skin preparation and conductive electrolytes at the skin-sensor interface. Another seldom-noted problem has been the need for a low impedance connection from the body to ground for cancellation of common-mode noise voltages. In this report, we describe EEG results acquired using EEG hardware based upon dry contact electrode technology, and which uses a proprietary common-mode follower (CMF) which allows a dry electrode to be used for the ground. This article presents results auditory evoked potential measurements using Wearable Sensing’s DSI-24 system simultaneously with conventional (wet) EEG electrodes. The correlations between wet and dry electrodes (averaged over 3 subjects) were 93.6% and 95.7% for F3-P3 and F4-P4, respectively.
A total of 3 subjects were selected for testing of QUASAR’s EEG hardware, according to an IRB-approved protocol. The auditory ERP task used a tone generation routine (200 tones on PC speakers, average interval 2 seconds) to stimulate ERP signals. A trigger signal was output for each tone on a single line on the parallel port of the PC to the trigger inputs of EEG hardware.
Subjects wore Wearable Sensing’s DSI-24 dry electrode EEG headset, which includes integrated dry electrode biosensors positioned at approximate standard International 10/20 electrode locations. Wet) Wet electrode measurements were acquired using Ag/AgCl EEG electrode cups filled with Grass EC2 conductive EEG paste (Astro-Med, West Warwick, RI) and attached to sites on the subject’s scalp. The electrode sites were cleaned with alcohol to remove fats and then abraded with NuPrep (Weaver & Co., Aurora, CO). Wet electrode signals were acquired using a commercial passive wet electrode EEG amplifier that has 24-bit resolution on 16 channels of EEG and a single trigger input.The wet electrodes were positioned at F1, F5, F2, F6, P1, P2, P5, P6 electrode sites and the ground and reference electrodes were placed at the right earlobe and pinna, respectively.
The F3-P3 and F4-P4 vectors were digitally calculated from the DSI-24 sensors. The equivalent signals for the wet electrodes were approximated by combining the wet electrode signals thus:
F3-P3 = (F1+F5)/2 – (P1+P5)/2 and F4-P4 = (F2+F6)/2 – (P2+P6)/2
Wet and Dry F3-P3 & F4-P4 signals were digitally filtered using Infinite Impulse Response (IIR) notch filters, and then bandpass filtered in a 1-40Hz bandwidth (-3dB). ERP epochs were obtained by taking an interval [-0.5s, +0.5s] around each trigger. Epochs in which the filtered signal magnitude exceeded 50 microV were rejected. The sample correlation coefficient was then calculated between the average dry electrode ERP and average wet electrode ERP signals.
The results for all three subjects are presented in the Figures to the right, which plot the average ERP signals in the interval from 500ms preceding the trigger to 500ms following a trigger. Correlations between wet and dry electrodes (averaged across 3 subjects) for the intervals shown are 93.6% and 95.7% for F3-P3 and F4-P4, respectively.
In addition, average signal to noise ratios (SNRs) for ERP amplitude over pre-trigger noise RMS voltage across 3 subjects and vectors were 11.8 +/- 5.5 and 12.6 +/-2.2 for dry and wet recordings respectively, indicating equivalent SNR.
Simultaneous measurements of ERP signals using dry electrode and wet electrodes excellent conservation of signal morphology between signals obtained from wet and dry electrodes; both in the pre-trigger “noise” segment and in the N100-P200 ERP component. This is evident both in a visual inspection of the traces presented in the illustrative Figures, and also by the fact that the correlation values exceed 90% for both anterior-posterior ERP signals and that the SNRs for both electrode technologies are equivalent.
For additional Information, please see our full report (322KB pdf) and the associated data files (15MB zip).