Quantitative Quality Assessment for EEG Data: A Mini Review

Electroencephalography (EEG) is an essential neuromonitoring modality, deeply integrated across scientific disciplines such as psychology, cognitive science, computational neuroscience, neurology, and psychiatry. Its relevance has surged with the rise of brain-computer interfaces. However, the potential of non-invasive EEG is hindered by compromised signal quality compared to invasive methods. The distinction between the modest EEG source amplitudes and the pronounced magnitudes of non-EEG physiological signals and environmental interferences complicates the analysis. The coexistence of subtle neural signals and prominent artifacts, both intrinsic and acquired, characterizes EEG signal processing. Various artifact management techniques have been proposed, yet the pursuit of EEG signal quality assessment remains underexplored. This mini-review addresses this gap by emphasizing the vital role of quality assessment in EEG recordings. The article highlights the significance of rigorous signal evaluation, emphasizing reliable EEG data. It also encapsulates evolving quantitative methodologies that bolster signal fidelity assessment. By delving into these aspects, the article presents a compact overview of ongoing advancements in quantitative EEG quality assessment techniques in the research field of EEG analysis and applications.