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

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Bibliographic Details
Title: EEG electrode setup optimization using feature extraction techniques for neonatal sleep state classification.
Authors: Siddiqa HA; Center for Intelligent Medical Electronics, Department of Electronic Engineering, School of Information Science and Technology, Fudan University, Shanghai, China., Qureshi MF; Department of Electrical Engineering, Namal University Mianwali, Mianwali, Pakistan., Khurshid A; Department of Electrical Engineering, Engineering Institute of Technology, Melbourne, VIC, Australia., Xu Y; Department of Neurology, Children's Hospital of Fudan University, National Children's Medical-Center, Shanghai, China., Wang L; Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China., Abbasi SF; Department of Electronic, Electrical and Systems Engineering, University of Birmingham, Birmingham, United Kingdom., Chen C; Human Phenome Institute, Fudan University, Shanghai, China., Chen W; School of Biomedical Engineering, The University of Sydney, Sydney, NSW, Australia.
Source: Frontiers in computational neuroscience [Front Comput Neurosci] 2025 Jan 31; Vol. 19, pp. 1506869. Date of Electronic Publication: 2025 Jan 31 (Print Publication: 2025).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101477956 Publication Model: eCollection Cited Medium: Print ISSN: 1662-5188 (Print) Linking ISSN: 16625188 NLM ISO Abbreviation: Front Comput Neurosci Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1662-5188
DOI:10.3389/fncom.2025.1506869