System Level Framework for Assessing the Accuracy of Neonatal EEG Acquisition

TL;DR

This paper introduces a clinical data simulation-based framework to evaluate the accuracy of neonatal EEG systems, enabling validation without involving vulnerable newborns.

Contribution

It presents a novel simulation method for assessing neonatal EEG acquisition accuracy, incorporating electrode and system models without requiring neonatal subjects.

Findings

Low-cost EEG systems can achieve clinical-grade recordings.

Dry electrodes, despite higher impedance, still provide accurate EEG data.

The framework effectively quantifies signal losses and quality metrics.

Abstract

Significant research has been conducted in recent years to design low-cost alternatives to the current EEG monitoring systems used in healthcare facilities. Testing such systems on a vulnerable population such as newborns is complicated due to ethical and regulatory considerations that slow down the technical development. This paper presents and validates a method for quantifying the accuracy of neonatal EEG acquisition systems and electrode technologies via clinical data simulations that do not require neonatal participants. The proposed method uses an extensive neonatal EEG database to simulate analogue signals, which are subsequently passed through electrical models of the skin-electrode interface, which are developed using wet and dry EEG electrode designs. The signal losses in the system are quantified at each stage of the acquisition process for electrode and acquisition board losses. SNR, correlation and noise values were calculated. The results verify that low-cost EEG acquisition systems are capable of obtaining clinical grade EEG. Although dry electrodes result in a significant increase in the skin-electrode impedance, accurate EEG recordings are still achievable.