Neonatologists and clinical neurophysiologists face challenges with the current electrodes used for long-duration amplitude-integrated electroencephalography (aEEG) in neonatal intensive care units (NICU), limiting the capacity to diagnose brain damage.
The objectives of this study were to develop methods for comparing the performance of different electrodes to be used in aEEG. The comparison was done between a newly designed neonate-specific electrode, aCUP-E, with commercial liquid gel electrodes used in amplitude-integrated electroencephalography (aEEG). The comparison included impedance stability, electrode survival, recording quality, usability, and satisfaction of NICU staff.
aEEG recordings with bipolar montage was used, with one hemisphere fitted with commercial electrodes and the other with aCUP-E electrodes, alternated among subjects. Continuous impedance and raw EEG data were collected over a minimum of 24 h, and signal processing was performed using Python and MATLAB.
aCUP-E electrodes demonstrated superior performance, including: Increased impedance stability and electrode survival, enhanced recording quality with fewer artifacts, high correlation in signal capture between electrodes during optimal brain activity segments, higher signal-to-noise ratio (SNR) across varying impedance levels, greater staff satisfaction and ease of use. Moreover, Kaplan-Meier curves indicated a higher survival rate for aCUP-E electrodes over 24 h compared to commercial electrodes. Impedance variability analysis showed statistically significant stability improvements for aCUP-E.
aCUP-E electrodes outperform commercial liquid gel electrodes in impedance stability, electrode survival, and recording quality. These results suggest that aCUP-E electrodes could significantly enhance aEEG utilization in diagnosing and treating neonatal brain conditions in NICUs. Future improvements to the aCUP-E electrode may further reduce artifacts and increase electrode longevity, potentially leading to a significant improvement in neonatal brain monitoring by means of aEEG.