{"id":"https://openalex.org/W4407045528","doi":"https://doi.org/10.3389/fncom.2025.1506869","title":"EEG electrode setup optimization using feature extraction techniques for neonatal sleep state classification","display_name":"EEG electrode setup optimization using feature extraction techniques for neonatal sleep state classification","publication_year":2025,"publication_date":"2025-01-31","ids":{"openalex":"https://openalex.org/W4407045528","doi":"https://doi.org/10.3389/fncom.2025.1506869","pmid":"https://pubmed.ncbi.nlm.nih.gov/39959920"},"language":"en","primary_location":{"id":"doi:10.3389/fncom.2025.1506869","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fncom.2025.1506869","pdf_url":"https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2025.1506869/pdf","source":{"id":"https://openalex.org/S19778766","display_name":"Frontiers in Computational Neuroscience","issn_l":"1662-5188","issn":["1662-5188"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computational Neuroscience","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2025.1506869/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028257758","display_name":"Hafza Ayesha Siddiqa","orcid":"https://orcid.org/0000-0002-2890-7830"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hafza Ayesha Siddiqa","raw_affiliation_strings":["Center for Intelligent Medical Electronics, Department of Electronic Engineering, School of Information Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Intelligent Medical Electronics, Department of Electronic Engineering, School of Information Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003039114","display_name":"Muhammad Farrukh Qureshi","orcid":"https://orcid.org/0000-0003-1167-349X"},"institutions":[{"id":"https://openalex.org/I2802902501","display_name":"Namal University","ror":"https://ror.org/00zcxra43","country_code":"PK","type":"education","lineage":["https://openalex.org/I2802902501"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Muhammad Farrukh Qureshi","raw_affiliation_strings":["Department of Electrical Engineering, Namal University Mianwali, Mianwali, Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Namal University Mianwali, Mianwali, Pakistan","institution_ids":["https://openalex.org/I2802902501"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Arsalan Khurshid","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arsalan Khurshid","raw_affiliation_strings":["Department of Electrical Engineering, Engineering Institute of Technology, Melbourne, VIC, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Engineering Institute of Technology, Melbourne, VIC, Australia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103034479","display_name":"Yan Xu","orcid":"https://orcid.org/0000-0003-2684-5741"},"institutions":[{"id":"https://openalex.org/I4210159329","display_name":"Children's Hospital of Fudan University","ror":"https://ror.org/05n13be63","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210159329"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Xu","raw_affiliation_strings":["Department of Neurology, Children's Hospital of Fudan University, National Children's Medical-Center, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Neurology, Children's Hospital of Fudan University, National Children's Medical-Center, Shanghai, China","institution_ids":["https://openalex.org/I4210159329"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101919966","display_name":"Laishuan Wang","orcid":"https://orcid.org/0000-0003-0527-8186"},"institutions":[{"id":"https://openalex.org/I4210159329","display_name":"Children's Hospital of Fudan University","ror":"https://ror.org/05n13be63","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210159329"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Laishuan Wang","raw_affiliation_strings":["Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I4210159329"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067603006","display_name":"Saadullah Farooq Abbasi","orcid":"https://orcid.org/0000-0001-9814-3023"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Saadullah Farooq Abbasi","raw_affiliation_strings":["Department of Electronic, Electrical and Systems Engineering, University of Birmingham, Birmingham, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic, Electrical and Systems Engineering, University of Birmingham, Birmingham, United Kingdom","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418553","display_name":"Chen Chen","orcid":"https://orcid.org/0000-0003-2541-6283"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Chen","raw_affiliation_strings":["Human Phenome Institute, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Human Phenome Institute, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100344582","display_name":"Wei Chen","orcid":"https://orcid.org/0000-0003-3720-718X"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Wei Chen","raw_affiliation_strings":["School of Biomedical Engineering, The University of Sydney, Sydney, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, The University of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5028257758","https://openalex.org/A5100344582","https://openalex.org/A5101919966"],"corresponding_institution_ids":["https://openalex.org/I129604602","https://openalex.org/I24943067","https://openalex.org/I4210159329"],"apc_list":{"value":2950,"currency":"USD","value_usd":2950},"apc_paid":{"value":2950,"currency":"USD","value_usd":2950},"fwci":7.2924,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.96871255,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"19","issue":null,"first_page":"1506869","last_page":"1506869"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/approximate-entropy","display_name":"Approximate entropy","score":0.7113094925880432},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.7098397016525269},{"id":"https://openalex.org/keywords/detrended-fluctuation-analysis","display_name":"Detrended fluctuation analysis","score":0.6564345955848694},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6326605677604675},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5851011276245117},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5777522325515747},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5562030076980591},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.527451753616333},{"id":"https://openalex.org/keywords/sleep-stages","display_name":"Sleep Stages","score":0.49546754360198975},{"id":"https://openalex.org/keywords/hurst-exponent","display_name":"Hurst exponent","score":0.4716978073120117},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.45206838846206665},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.44832155108451843},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25794869661331177},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23077023029327393},{"id":"https://openalex.org/keywords/polysomnography","display_name":"Polysomnography","score":0.21171700954437256},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.20790019631385803},{"id":"https://openalex.org/keywords/psychiatry","display_name":"Psychiatry","score":0.09730646014213562}],"concepts":[{"id":"https://openalex.org/C86859247","wikidata":"https://www.wikidata.org/wiki/Q4781760","display_name":"Approximate entropy","level":3,"score":0.7113094925880432},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.7098397016525269},{"id":"https://openalex.org/C21689155","wikidata":"https://www.wikidata.org/wiki/Q2451452","display_name":"Detrended fluctuation analysis","level":3,"score":0.6564345955848694},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6326605677604675},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5851011276245117},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5777522325515747},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5562030076980591},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.527451753616333},{"id":"https://openalex.org/C2910364982","wikidata":"https://www.wikidata.org/wiki/Q35831","display_name":"Sleep Stages","level":4,"score":0.49546754360198975},{"id":"https://openalex.org/C96835011","wikidata":"https://www.wikidata.org/wiki/Q1638718","display_name":"Hurst exponent","level":2,"score":0.4716978073120117},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.45206838846206665},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.44832155108451843},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25794869661331177},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23077023029327393},{"id":"https://openalex.org/C2778205975","wikidata":"https://www.wikidata.org/wiki/Q1754874","display_name":"Polysomnography","level":3,"score":0.21171700954437256},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.20790019631385803},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.09730646014213562},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3389/fncom.2025.1506869","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fncom.2025.1506869","pdf_url":"https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2025.1506869/pdf","source":{"id":"https://openalex.org/S19778766","display_name":"Frontiers in Computational Neuroscience","issn_l":"1662-5188","issn":["1662-5188"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computational Neuroscience","raw_type":"journal-article"},{"id":"pmid:39959920","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39959920","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in computational neuroscience","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11825521","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11825521","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11825521/pdf/fncom-19-1506869.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Front Comput Neurosci","raw_type":"Text"},{"id":"pmh:oai:pure.atira.dk:publications/8294ef4d-7111-4086-888f-ddef325c3fa6","is_oa":true,"landing_page_url":"https://research.birmingham.ac.uk/en/publications/8294ef4d-7111-4086-888f-ddef325c3fa6","pdf_url":"https://pure-oai.bham.ac.uk/ws/files/257332135/fncom-19-1506869.pdf","source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Siddiqa, H A, Qureshi, M F, Khurshid, A, Xu, Y, Wang, L, Abbasi, S F, Chen, C & Chen, W 2025, 'EEG electrode setup optimization using feature extraction techniques for neonatal sleep state classification', Frontiers in Computational Neuroscience, vol. 19, 1506869. https://doi.org/10.3389/fncom.2025.1506869","raw_type":"article"},{"id":"pmh:oai:doaj.org/article:2f856547704e49aeb57e28b4963d7621","is_oa":true,"landing_page_url":"https://doaj.org/article/2f856547704e49aeb57e28b4963d7621","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Computational Neuroscience, Vol 19 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/fncom.2025.1506869","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fncom.2025.1506869","pdf_url":"https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2025.1506869/pdf","source":{"id":"https://openalex.org/S19778766","display_name":"Frontiers in Computational Neuroscience","issn_l":"1662-5188","issn":["1662-5188"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computational Neuroscience","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6000000238418579,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321851","display_name":"Fudan University","ror":"https://ror.org/013q1eq08"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4407045528.pdf"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W2017689092","https://openalex.org/W2029520770","https://openalex.org/W2062439387","https://openalex.org/W2089468765","https://openalex.org/W2111910994","https://openalex.org/W2132271223","https://openalex.org/W2151669809","https://openalex.org/W2320406861","https://openalex.org/W2331984239","https://openalex.org/W2589719932","https://openalex.org/W2595353633","https://openalex.org/W2604096629","https://openalex.org/W2759717405","https://openalex.org/W2793410326","https://openalex.org/W2800788706","https://openalex.org/W2888299873","https://openalex.org/W2985790470","https://openalex.org/W2999292155","https://openalex.org/W3003721337","https://openalex.org/W3090611074","https://openalex.org/W3097754050","https://openalex.org/W3116326714","https://openalex.org/W3153528690","https://openalex.org/W3156063572","https://openalex.org/W3158417192","https://openalex.org/W3158818505","https://openalex.org/W3172444956","https://openalex.org/W3183434091","https://openalex.org/W3207009339","https://openalex.org/W4200554111","https://openalex.org/W4220845605","https://openalex.org/W4226247439","https://openalex.org/W4241366218","https://openalex.org/W4243064372","https://openalex.org/W4282946590","https://openalex.org/W4304013913","https://openalex.org/W4309164566","https://openalex.org/W4327955596","https://openalex.org/W4361281686","https://openalex.org/W4365443956","https://openalex.org/W4380089224","https://openalex.org/W4380680601","https://openalex.org/W4383816740","https://openalex.org/W4385245566","https://openalex.org/W4385812986","https://openalex.org/W4387350590","https://openalex.org/W4389144589","https://openalex.org/W4391364486","https://openalex.org/W4391791406","https://openalex.org/W4394779318","https://openalex.org/W4399851983","https://openalex.org/W4400906709","https://openalex.org/W4402586195","https://openalex.org/W6739901393","https://openalex.org/W6745410362","https://openalex.org/W6780010607","https://openalex.org/W6789177658"],"related_works":["https://openalex.org/W4321505114","https://openalex.org/W2401810189","https://openalex.org/W2057384585","https://openalex.org/W2035064929","https://openalex.org/W2795419853","https://openalex.org/W2911012399","https://openalex.org/W2073997720","https://openalex.org/W2997775184","https://openalex.org/W4291518329","https://openalex.org/W2136039781"],"abstract_inverted_index":{"An":[0,46,110],"optimal":[1,205],"arrangement":[2],"of":[3,15,60,78,148,156,226,254],"electrodes":[4,163,173],"during":[5],"data":[6],"collection":[7],"is":[8,114,164],"essential":[9],"for":[10,160,170],"gaining":[11],"a":[12,37,153,230,238],"deeper":[13],"understanding":[14],"neonatal":[16,43,216],"sleep":[17,44,198,227,263,266],"and":[18,28,57,69,85,91,104,128,183,244,256,259,268],"assessing":[19],"cognitive":[20],"health":[21],"in":[22,88,196],"order":[23],"to":[24,67,137,214],"reduce":[25,29],"technical":[26],"complexity":[27],"skin":[30],"irritation":[31],"risks.":[32],"Using":[33],"electroencephalography":[34],"(EEG)":[35],"data,":[36],"long-short-term":[38],"memory":[39],"(LSTM)":[40],"classifier":[41],"categorizes":[42],"states.":[45],"16,803":[47],"30-second":[48],"segment":[49],"was":[50],"collected":[51],"from":[52],"64":[53],"infants":[54],"between":[55,112],"36":[56],"43":[58],"weeks":[59],"age":[61],"at":[62,247],"Fudan":[63],"University":[64],"Children's":[65],"Hospital":[66],"train":[68],"test":[70],"the":[71,76,89,117,122,141,248,252],"proposed":[72],"model.":[73],"To":[74],"enhance":[75],"performance":[77,246],"an":[79,145,193],"LSTM-based":[80],"classification":[81],"model,":[82],"94":[83],"linear":[84,258],"nonlinear":[86,260],"features":[87,97,125,261],"time":[90,255],"frequency":[92],"domains":[93],"with":[94,152],"three":[95],"novel":[96],"(Detrended":[98],"Fluctuation":[99],"Analysis":[100],"(DFA),":[101],"Lyapunov":[102],"exponent,":[103],"multiscale":[105],"fluctuation":[106],"entropy)":[107],"are":[108,126,180],"extracted.":[109],"imbalance":[111],"classes":[113],"solved":[115],"using":[116,130,237],"SMOTE":[118],"technique.":[119],"In":[120,135],"addition,":[121],"most":[123],"significant":[124],"identified":[127],"prioritized":[129],"principal":[131],"component":[132],"analysis":[133],"(PCA).":[134],"comparison":[136],"other":[138],"single":[139,239],"channels,":[140],"C3":[142],"channel":[143],"has":[144],"accuracy":[146,159],"value":[147,155],"80.75%":[149],"\u00b1":[150,167,175],"0.82%,":[151],"kappa":[154,178],"0.76.":[157,184],"Classification":[158],"four":[161,171],"left-side":[162],"higher":[165],"(82.71%":[166],"0.88%)":[168],"than":[169],"right-side":[172],"(81.14%":[174],"0.77%),":[176],"while":[177],"values":[179],"respectively":[181],"0.78":[182],"Study":[185],"results":[186],"suggest":[187],"that":[188],"specific":[189],"EEG":[190],"channels":[191],"play":[192],"important":[194],"role":[195],"determining":[197],"stage":[199],"classification,":[200],"as":[201,203],"well":[202],"suggesting":[204],"electrode":[206],"configuration.":[207],"Moreover,":[208],"this":[209,232],"research":[210],"can":[211,222,270],"be":[212,271],"used":[213],"improve":[215],"care":[217],"by":[218],"monitoring":[219],"sleep,":[220],"which":[221],"allow":[223],"early":[224],"detection":[225],"disorders.":[228],"As":[229],"result,":[231],"study":[233],"captures":[234],"information":[235],"effectively":[236],"channel,":[240],"reducing":[241],"computing":[242],"load":[243],"maintaining":[245],"same":[249],"time.":[250],"With":[251],"incorporation":[253],"frequency-domain":[257],"into":[262],"staging,":[264],"newborn":[265],"dynamics":[267],"irregularities":[269],"better":[272],"understood.":[273]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3}],"updated_date":"2026-05-08T15:41:06.802602","created_date":"2025-10-10T00:00:00"}