{"id":"https://openalex.org/W4312357292","doi":"https://doi.org/10.1109/icarm54641.2022.9959633","title":"An EEG-informed Hemodynamic Response Modeling Method for fNIRS Signals","display_name":"An EEG-informed Hemodynamic Response Modeling Method for fNIRS Signals","publication_year":2022,"publication_date":"2022-07-09","ids":{"openalex":"https://openalex.org/W4312357292","doi":"https://doi.org/10.1109/icarm54641.2022.9959633"},"language":"en","primary_location":{"id":"doi:10.1109/icarm54641.2022.9959633","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarm54641.2022.9959633","pdf_url":null,"source":{"id":"https://openalex.org/S4363608069","display_name":"2022 International Conference on Advanced Robotics and Mechatronics (ICARM)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Advanced Robotics and Mechatronics (ICARM)","raw_type":"proceedings-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/A5085117641","display_name":"Jianeng Lin","orcid":"https://orcid.org/0000-0002-0811-9423"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianeng Lin","raw_affiliation_strings":["Nankai University,College of Artificial Intelligence,Tianjin,China,300350","Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Nankai University,College of Artificial Intelligence,Tianjin,China,300350","institution_ids":["https://openalex.org/I205237279"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000666851","display_name":"Jiewei Lu","orcid":"https://orcid.org/0000-0003-3905-9571"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiewei Lu","raw_affiliation_strings":["Nankai University,College of Artificial Intelligence,Tianjin,China,300350","Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Nankai University,College of Artificial Intelligence,Tianjin,China,300350","institution_ids":["https://openalex.org/I205237279"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068559464","display_name":"Zhilin Shu","orcid":"https://orcid.org/0009-0008-0186-2418"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhilin Shu","raw_affiliation_strings":["Nankai University,College of Artificial Intelligence,Tianjin,China,300350","Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Nankai University,College of Artificial Intelligence,Tianjin,China,300350","institution_ids":["https://openalex.org/I205237279"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088919891","display_name":"Ningbo Yu","orcid":"https://orcid.org/0000-0003-2159-3055"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ningbo Yu","raw_affiliation_strings":["Nankai University,College of Artificial Intelligence,Tianjin,China,300350","Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Nankai University,College of Artificial Intelligence,Tianjin,China,300350","institution_ids":["https://openalex.org/I205237279"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100439073","display_name":"Jianda Han","orcid":"https://orcid.org/0000-0002-9664-4534"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianda Han","raw_affiliation_strings":["Nankai University,College of Artificial Intelligence,Tianjin,China,300350","Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Nankai University,College of Artificial Intelligence,Tianjin,China,300350","institution_ids":["https://openalex.org/I205237279"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5085117641"],"corresponding_institution_ids":["https://openalex.org/I205237279"],"apc_list":null,"apc_paid":null,"fwci":0.3214,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5054315,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"6","issue":null,"first_page":"617","last_page":"622"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9995999932289124,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9983999729156494,"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/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/electroencephalography","display_name":"Electroencephalography","score":0.7299829721450806},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6277548670768738},{"id":"https://openalex.org/keywords/haemodynamic-response","display_name":"Haemodynamic response","score":0.6254081726074219},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35983413457870483},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.2900691628456116},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.193804532289505},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.11031192541122437},{"id":"https://openalex.org/keywords/blood-pressure","display_name":"Blood pressure","score":0.09454011917114258},{"id":"https://openalex.org/keywords/heart-rate","display_name":"Heart rate","score":0.06720763444900513}],"concepts":[{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.7299829721450806},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6277548670768738},{"id":"https://openalex.org/C26170363","wikidata":"https://www.wikidata.org/wiki/Q1981408","display_name":"Haemodynamic response","level":4,"score":0.6254081726074219},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35983413457870483},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2900691628456116},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.193804532289505},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.11031192541122437},{"id":"https://openalex.org/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.09454011917114258},{"id":"https://openalex.org/C2777953023","wikidata":"https://www.wikidata.org/wiki/Q1073121","display_name":"Heart rate","level":3,"score":0.06720763444900513},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icarm54641.2022.9959633","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarm54641.2022.9959633","pdf_url":null,"source":{"id":"https://openalex.org/S4363608069","display_name":"2022 International Conference on Advanced Robotics and Mechatronics (ICARM)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Advanced Robotics and Mechatronics (ICARM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2036902953","https://openalex.org/W2052984950","https://openalex.org/W2072067437","https://openalex.org/W2072235982","https://openalex.org/W2092890379","https://openalex.org/W2096545952","https://openalex.org/W2104591424","https://openalex.org/W2128001879","https://openalex.org/W2128495200","https://openalex.org/W2329076961","https://openalex.org/W2477215248","https://openalex.org/W2610586781","https://openalex.org/W2913362696","https://openalex.org/W2974896981","https://openalex.org/W3004612918","https://openalex.org/W3008922215","https://openalex.org/W3012307454","https://openalex.org/W3100936064","https://openalex.org/W3196438322","https://openalex.org/W6768525556"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2922348724","https://openalex.org/W200322357","https://openalex.org/W2390279801","https://openalex.org/W2130428257","https://openalex.org/W4308951944","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109"],"abstract_inverted_index":{"Combining":[0],"electroencephalography":[1],"(EEG)":[2],"and":[3,24,52,97,152,179],"functional":[4],"near-infrared":[5],"spectroscopy":[6],"(fNIRS)":[7],"is":[8,36,50],"a":[9,46,83,87,131,165,180],"feasible":[10],"way":[11,167],"to":[12,61,76,90,168],"understand":[13],"the":[14,27,32,40,54,59,62,95,98,101,109,123,143,150,153,158,170,185],"neural":[15],"mechanism":[16],"of":[17,58,94,100,113,172],"human":[18],"brain":[19],"function":[20,43,85,104],"for":[21,183],"their":[22],"complementarity":[23],"compatibility.":[25],"In":[26,64],"canonical":[28,159],"fNIRS":[29,78,121,173],"linear":[30,174],"model,":[31],"stimulus-evoked":[33],"hemodynamic":[34,41],"response":[35,42],"modeled":[37],"by":[38],"convolving":[39],"(HRF)":[44],"with":[45,86,120,136,157],"stimulus":[47,84,103],"function,":[48],"which":[49,116],"boxcar-shaped":[51],"ignores":[53],"dynamic":[55],"stimulation":[56],"degree":[57],"task":[60],"brain.":[63],"this":[65],"study,":[66],"we":[67,81],"propose":[68],"that":[69,142],"EEG\u2019s":[70],"time-frequency":[71],"features":[72],"can":[73,105],"be":[74,106],"used":[75],"optimize":[77,169],"analysis.":[79],"Specifically,":[80],"designed":[82],"piecewise":[88,102],"structure":[89],"represent":[91],"different":[92],"stages":[93],"task,":[96],"parameters":[99],"calculated":[107],"from":[108],"event-related":[110],"desynchronization":[111],"(ERD)":[112],"EEG":[114],"data,":[115],"were":[117],"simultaneously":[118],"recorded":[119],"during":[122],"task.":[124],"The":[125,161],"proposed":[126,162],"method":[127,163],"was":[128],"verified":[129],"in":[130,155,176],"grip":[132],"force":[133],"tracking":[134],"experiment":[135],"16":[137],"participants.":[138],"Our":[139],"results":[140],"indicated":[141],"EEG-informed":[144],"modeling":[145,175],"framework":[146],"could":[147],"significantly":[148],"improve":[149],"correlation":[151],"laterality":[154],"comparison":[156],"method.":[160],"provides":[164],"promising":[166],"performance":[171],"multi-stage":[177],"tasks":[178],"novel":[181],"solution":[182],"investigating":[184],"neurovascular":[186],"coupling.":[187]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
