Analysis of a low-cost EEG monitoring system and dry electrodes toward clinical use in the neonatal ICU

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O'Sullivan, Mark
Temko, Andriy
Bocchino, Andrea
O'Mahony, Conor
Boylan, Geraldine B.
Popovici, Emanuel M.
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Electroencephalography (EEG) is an important clinical tool for monitoring neurological health. However, the required equipment, expertise, and patient preparation inhibits its use outside of tertiary care. Non-experts struggle to obtain high-quality EEG due to its low amplitude and artefact susceptibility. Wet electrodes are currently used, which require abrasive/conductive gels to reduce skin-electrode impedance. Advances in dry electrodes, which do not require gels, have simplified this process. However, the assessment of dry electrodes on neonates is limited due to health and safety barriers. This study presents a simulation framework for assessing the quality of EEG systems using a neonatal EEG database, without the use of human participants. The framework is used to evaluate a low-cost EEG acquisition system and compare performance of wet and dry (Micro Transdermal Interface Platforms (MicroTIPs), g.tec-g.SAHARA) electrodes using accurately acquired impedance models. A separate experiment assessing the electrodes on adult participants was conducted to verify the simulation framework’s efficacy. Dry electrodes have higher impedance than wet electrodes, causing a reduction in signal quality. However, MicroTIPs perform comparably to wet electrodes at the frontal region and g.tec-g.SAHARA performs well at the occipital region. Using the simulation framework, a 25dB signal-to-noise ratio (SNR) was obtained for the low-cost EEG system. The tests on adults closely matched the simulated results.
Neonatal EEG , EEG electrode , Dry electrode , MicroTIPs , Microneedles , G.tec
O’Sullivan, M., Temko, A., Bocchino, A., O’Mahony, C., Boylan, G. and Popovici, E. (2019) 'Analysis of a Low-Cost EEG Monitoring System and Dry Electrodes toward Clinical Use in the Neonatal ICU', Sensors, 19(11), 2637. (16pp.) DOI: 10.3390/s19112637