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

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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