{"id":"https://openalex.org/W2946213036","doi":"https://doi.org/10.1109/jbhi.2019.2917093","title":"State Estimation of Hemodynamic Model for fMRI Under Confounds: SSM Method","display_name":"State Estimation of Hemodynamic Model for fMRI Under Confounds: SSM Method","publication_year":2019,"publication_date":"2019-05-15","ids":{"openalex":"https://openalex.org/W2946213036","doi":"https://doi.org/10.1109/jbhi.2019.2917093","mag":"2946213036"},"language":"en","primary_location":{"id":"doi:10.1109/jbhi.2019.2917093","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2019.2917093","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010785909","display_name":"Haifeng Wu","orcid":"https://orcid.org/0000-0002-6370-8415"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haifeng Wu","raw_affiliation_strings":["Yunnan Minzu University, Kunming, China"],"raw_orcid":"https://orcid.org/0000-0002-6370-8415","affiliations":[{"raw_affiliation_string":"Yunnan Minzu University, Kunming, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089780363","display_name":"Mingzhi Lu","orcid":"https://orcid.org/0000-0001-6683-7880"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingzhi Lu","raw_affiliation_strings":["Yunnan Minzu University, Kunming, China"],"raw_orcid":"https://orcid.org/0000-0001-6683-7880","affiliations":[{"raw_affiliation_string":"Yunnan Minzu University, Kunming, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100616980","display_name":"Yu Zeng","orcid":"https://orcid.org/0009-0006-1734-9876"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zeng","raw_affiliation_strings":["Yunnan Minzu University, Kunming, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yunnan Minzu University, Kunming, China","institution_ids":["https://openalex.org/I145897649"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5010785909"],"corresponding_institution_ids":["https://openalex.org/I145897649"],"apc_list":null,"apc_paid":null,"fwci":0.124,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.46478003,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"24","issue":"3","first_page":"804","last_page":"814"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9969000220298767,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9969000220298767,"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/T11700","display_name":"Hemodynamic Monitoring and Therapy","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10924","display_name":"Cardiovascular Health and Disease Prevention","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.6683549284934998},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6256006956100464},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6099943518638611},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.609228789806366},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.542229413986206},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5248020887374878},{"id":"https://openalex.org/keywords/functional-magnetic-resonance-imaging","display_name":"Functional magnetic resonance imaging","score":0.48360055685043335},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.4510188102722168},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4470962882041931},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.41030025482177734},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4070127308368683},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2881033420562744},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.23635971546173096},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19463449716567993},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.13977482914924622},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.12146571278572083}],"concepts":[{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6683549284934998},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6256006956100464},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6099943518638611},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.609228789806366},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.542229413986206},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5248020887374878},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.48360055685043335},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.4510188102722168},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4470962882041931},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.41030025482177734},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4070127308368683},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2881033420562744},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.23635971546173096},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19463449716567993},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.13977482914924622},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.12146571278572083},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jbhi.2019.2917093","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2019.2917093","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.6000000238418579,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G3879887916","display_name":null,"funder_award_id":"61762093","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8578313971","display_name":null,"funder_award_id":"2018FA036","funder_id":"https://openalex.org/F4320332533","funder_display_name":"Applied Basic Research Foundation of Yunnan Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320332533","display_name":"Applied Basic Research Foundation of Yunnan Province","ror":"https://ror.org/030jhb479"},{"id":"https://openalex.org/F4320334919","display_name":"Program for Innovative Research Team of Ningbo Novel Photoelectric Materials and Devices","ror":"https://ror.org/03et85d35"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W76515229","https://openalex.org/W1528119265","https://openalex.org/W1978510898","https://openalex.org/W1992272716","https://openalex.org/W2001366834","https://openalex.org/W2003035294","https://openalex.org/W2009494091","https://openalex.org/W2024091024","https://openalex.org/W2037805683","https://openalex.org/W2039866424","https://openalex.org/W2040891197","https://openalex.org/W2049325056","https://openalex.org/W2054429734","https://openalex.org/W2066650412","https://openalex.org/W2083136232","https://openalex.org/W2085878569","https://openalex.org/W2091991315","https://openalex.org/W2117663940","https://openalex.org/W2123586737","https://openalex.org/W2125923236","https://openalex.org/W2130982683","https://openalex.org/W2139447054","https://openalex.org/W2149153247","https://openalex.org/W2155734932","https://openalex.org/W2158304243","https://openalex.org/W2159784657","https://openalex.org/W2161337392","https://openalex.org/W2189672817","https://openalex.org/W2203624646","https://openalex.org/W2238108400","https://openalex.org/W2802309997","https://openalex.org/W6652925209","https://openalex.org/W6683285222","https://openalex.org/W6687463137"],"related_works":["https://openalex.org/W1978572805","https://openalex.org/W2383807498","https://openalex.org/W1997992934","https://openalex.org/W1987225439","https://openalex.org/W4238188170","https://openalex.org/W2125114371","https://openalex.org/W2360090175","https://openalex.org/W2886934452","https://openalex.org/W1489099099","https://openalex.org/W2024369332"],"abstract_inverted_index":{"Through":[0],"hemodynamic":[1,53],"models,":[2],"the":[3,23,29,32,35,40,110,113,122,130,142],"change":[4],"of":[5,31,112],"neuronal":[6,36],"state":[7,37,60,65],"can":[8],"be":[9,79],"estimated":[10],"from":[11,50],"functional":[12],"magnetic":[13],"resonance":[14],"imaging":[15],"(fMRI)":[16],"signals.":[17],"Usually,":[18],"there":[19],"are":[20],"confounds":[21,83,106],"in":[22,92,133],"fMRI":[24],"signal,":[25],"which":[26],"will":[27],"degrade":[28],"performance":[30,111],"estimation":[33,61,137],"for":[34],"change.":[38],"For":[39],"reason,":[41],"this":[42,56,93,134],"paper":[43,135],"introduces":[44],"a":[45,51,58,64,75,82,97],"state-space":[46],"model":[47,99],"with":[48],"confounds,":[49],"conventional":[52],"model.":[54],"In":[55],"model,":[57],"successive":[59],"method":[62],"requires":[63],"value":[66],"vector,":[67],"an":[68,71],"error":[69,138],"covariance,":[70,73],"innovation":[72],"and":[74,104],"cross":[76],"covariance":[77],"to":[78,100,108,139,147],"re-derived.":[80],"Thus,":[81],"square-root":[84],"cubature":[85],"Kalman":[86],"smoothing":[87],"(CSCKS)":[88],"algorithm":[89,144],"is":[90,125],"proposed":[91,114,132],"paper.":[94],"We":[95],"use":[96],"Balloon-Windkessel":[98],"generate":[101],"simulation":[102],"data":[103],"add":[105],"signals":[107],"evaluate":[109],"algorithm.":[115],"The":[116],"experiment":[117],"results":[118],"show":[119],"that":[120],"when":[121],"signal-to-interference":[123],"ratio":[124],"less":[126],"than":[127],"21":[128],"dB,":[129],"CSCKS":[131],"reduced":[136,145],"16%,":[140],"whereas":[141],"traditional":[143],"it":[146],"only":[148],"73%.":[149]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2019-05-29T00:00:00"}