EEG electrode setup optimization using feature extraction techniques for neonatal sleep state classification

An optimal arrangement of electrodes during data collection is essential for gaining a deeper understanding of neonatal sleep and assessing cognitive health in order to reduce technical complexity and reduce skin irritation risks. Using electroencephalography (EEG) data, a long-short-term memory (LS...

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Bibliographic Details
Main Authors:	Hafza Ayesha Siddiqa, Muhammad Farrukh Qureshi, Arsalan Khurshid, Yan Xu, Laishuan Wang, Saadullah Farooq Abbasi, Chen Chen, Wei Chen
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2025-01-01
Series:	Frontiers in Computational Neuroscience
Subjects:	EEG sleep analysis neonatal sleep state classification principal component analysis SMOTE LSTM
Online Access:	https://www.frontiersin.org/articles/10.3389/fncom.2025.1506869/full
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EEG electrode setup optimization using feature extraction techniques for neonatal sleep state classification

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