Quantitative Quality Assessment for EEG Data: A Mini Review

Chun Shu Wei*

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

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.

原文English
主出版物標題2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023
發行者Institute of Electrical and Electronics Engineers Inc.
頁面64-68
頁數5
ISBN(電子)9781665430654
DOIs
出版狀態Published - 2023
事件2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023 - Mexico City, Mexico
持續時間: 5 12月 20238 12月 2023

出版系列

名字2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

Conference

Conference2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023
國家/地區Mexico
城市Mexico City
期間5/12/238/12/23

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