{"id":"https://openalex.org/W4417282952","doi":"https://doi.org/10.1109/gcce65946.2025.11275045","title":"Brain State Discrimination Performance of Ensemble Learning Model Based on Spatiotemporal Features from Cerebral Blood Flow for Brain-Computer Interface","display_name":"Brain State Discrimination Performance of Ensemble Learning Model Based on Spatiotemporal Features from Cerebral Blood Flow for Brain-Computer Interface","publication_year":2025,"publication_date":"2025-09-23","ids":{"openalex":"https://openalex.org/W4417282952","doi":"https://doi.org/10.1109/gcce65946.2025.11275045"},"language":"en","primary_location":{"id":"doi:10.1109/gcce65946.2025.11275045","doi":"https://doi.org/10.1109/gcce65946.2025.11275045","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce65946.2025.11275045","pdf_url":null,"source":{"id":"https://openalex.org/S4363607800","display_name":"IEEE Global Conference on Consumer Electronics (GCCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2025 IEEE 14th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5081287479","display_name":"Akira Masuo","orcid":"https://orcid.org/0000-0003-0152-4781","observed_orcids":["https://orcid.org/0000-0003-0152-4781"]},"institutions":[{"id":"https://openalex.org/I11317238","display_name":"Seijoh University","ror":"https://ror.org/0085wxm22","country_code":"JP","type":"education","lineage":["https://openalex.org/I11317238"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akira Masuo","raw_affiliation_strings":["Seijoh University,Faculty of Business Administration,Nagoya,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seijoh University,Faculty of Business Administration,Nagoya,Japan","institution_ids":["https://openalex.org/I11317238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071125463","display_name":"Takuto Sakuma","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takuto Sakuma","raw_affiliation_strings":["Nagoya Institute of Technology,Graduate School of Engineering,Nagoya,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagoya Institute of Technology,Graduate School of Engineering,Nagoya,Japan","institution_ids":["https://openalex.org/I197274945"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088832778","display_name":"Sh\u014dhei Kato","orcid":"https://orcid.org/0000-0003-4130-2729","observed_orcids":["https://orcid.org/0000-0003-4130-2729"]},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shohei Kato","raw_affiliation_strings":["Nagoya Institute of Technology,Graduate School of Engineering,Nagoya,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagoya Institute of Technology,Graduate School of Engineering,Nagoya,Japan","institution_ids":["https://openalex.org/I197274945"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"966","last_page":"968"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9887999892234802,"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":0.9887999892234802,"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":0.008799999952316284,"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"}},{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.00039999998989515007,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/brain-computer-interface","display_name":"brain-computer interface","score":0.9990000128746033},{"id":"https://openalex.org/keywords/near-infrared-spectroscopy","display_name":"near-infrared spectroscopy","score":0.9440000057220459},{"id":"https://openalex.org/keywords/cerebral-blood-flow","display_name":"cerebral blood flow","score":0.9789999723434448},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"ensemble learning","score":0.890999972820282},{"id":"https://openalex.org/keywords/majority-voting","display_name":"majority voting","score":0.9359999895095825},{"id":"https://openalex.org/keywords/spatio-temporal-features","display_name":"spatio-temporal features","score":0.9639999866485596},{"id":"https://openalex.org/keywords/amyotrophic-lateral-sclerosis","display_name":"amyotrophic lateral sclerosis","score":0.9229999780654907},{"id":"https://openalex.org/keywords/musical-imagery","display_name":"musical imagery","score":0.7829999923706055},{"id":"https://openalex.org/keywords/mental-arithmetic","display_name":"mental arithmetic","score":0.9919999837875366},{"id":"https://openalex.org/keywords/neurological-disorders","display_name":"neurological disorders","score":0.5180000066757202},{"id":"https://openalex.org/keywords/communication-aids","display_name":"communication aids","score":0.4129999876022339}],"concepts":[{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.7857999801635742},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.6161999702453613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5720999836921692},{"id":"https://openalex.org/C157767197","wikidata":"https://www.wikidata.org/wiki/Q886843","display_name":"Cerebral blood flow","level":2,"score":0.534600019454956},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5224000215530396},{"id":"https://openalex.org/C2780596555","wikidata":"https://www.wikidata.org/wiki/Q206901","display_name":"Amyotrophic lateral sclerosis","level":3,"score":0.5112000107765198},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5065000057220459},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44609999656677246},{"id":"https://openalex.org/C2780640218","wikidata":"https://www.wikidata.org/wiki/Q8277","display_name":"Multiple sclerosis","level":2,"score":0.42399999499320984},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4147999882698059},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3772999942302704},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.3763999938964844},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3693000078201294},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.33880001306533813},{"id":"https://openalex.org/C2984915365","wikidata":"https://www.wikidata.org/wiki/Q5141203","display_name":"Cognitive impairment","level":3,"score":0.3382999897003174},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.30809998512268066},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2987000048160553},{"id":"https://openalex.org/C120843803","wikidata":"https://www.wikidata.org/wiki/Q4955807","display_name":"Brain activity and meditation","level":3,"score":0.26089999079704285},{"id":"https://openalex.org/C119653847","wikidata":"https://www.wikidata.org/wiki/Q1327780","display_name":"Elementary cognitive task","level":3,"score":0.25540000200271606},{"id":"https://openalex.org/C2780317758","wikidata":"https://www.wikidata.org/wiki/Q3339235","display_name":"Neurological disorder","level":3,"score":0.25440001487731934},{"id":"https://openalex.org/C2780645631","wikidata":"https://www.wikidata.org/wiki/Q671554","display_name":"Stroke (engine)","level":2,"score":0.2515000104904175},{"id":"https://openalex.org/C2779429828","wikidata":"https://www.wikidata.org/wiki/Q3968640","display_name":"Mental state","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce65946.2025.11275045","doi":"https://doi.org/10.1109/gcce65946.2025.11275045","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce65946.2025.11275045","pdf_url":null,"source":{"id":"https://openalex.org/S4363607800","display_name":"IEEE Global Conference on Consumer Electronics (GCCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2025 IEEE 14th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8048999905586243,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2045561515","https://openalex.org/W2062500193","https://openalex.org/W2755510477","https://openalex.org/W4399517715"],"related_works":["https://openalex.org/W3009418875","https://openalex.org/W4399517715","https://openalex.org/W2900436145","https://openalex.org/W2062500193","https://openalex.org/W3010615990","https://openalex.org/W3096468965","https://openalex.org/W3096623455","https://openalex.org/W2315570588","https://openalex.org/W2740721782","https://openalex.org/W2183740617"],"abstract_inverted_index":{"Brain-computer":[0],"interface":[1],"(BCI)":[2],"is":[3],"gaining":[4],"attention":[5],"as":[6,98],"a":[7,33],"new":[8],"means":[9],"of":[10,22,116,123],"expression":[11],"for":[12,89,130,139],"patients":[13,140],"with":[14,35,44,65,95,141],"neurological":[15,36,142],"disorders.":[16],"This":[17,125],"study":[18],"evaluated":[19],"the":[20,50,77,102,128,132],"performance":[21],"brain":[23,146],"state":[24],"discrimination":[25],"using":[26,92,107,144],"near-infrared":[27],"spectroscopy":[28],"(NIRS)":[29],"signals":[30,54],"measured":[31,56],"from":[32,76],"patient":[34,43],"disorders":[37,143],"to":[38,134,136],"apply":[39],"BCI.":[40],"A":[41,80],"single":[42],"amyotrophic":[45],"lateral":[46],"sclerosis":[47],"participated":[48],"in":[49],"study,":[51],"and":[52,62,71,101],"NIRS":[53,78],"were":[55,74],"during":[57],"two":[58],"tasks,":[59],"mental":[60],"arithmetic":[61],"music":[63],"imagery,":[64],"24":[66],"trials":[67],"each.":[68],"Time-domain":[69],"features":[70,73],"spectral-domain":[72],"extracted":[75],"signals.":[79],"model":[81,111],"was":[82,105],"constructed":[83],"by":[84],"integrating":[85],"weak":[86],"learners":[87],"created":[88],"each":[90],"channel":[91],"majority":[93],"voting,":[94],"cognitive":[96],"tasks":[97],"teacher":[99],"labels,":[100],"classification":[103],"accuracy":[104,122],"calculated":[106],"24-fold":[108],"cross-validation.":[109],"The":[110],"correctly":[112],"classified":[113],"39":[114],"out":[115],"48":[117],"trials,":[118],"achieving":[119],"an":[120],"average":[121],"81%.":[124],"method":[126],"demonstrates":[127],"potential":[129],"applying":[131],"technique":[133],"BCI":[135],"enable":[137],"communication":[138],"residual":[145],"function.":[147]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2025-12-12T00:00:00"}
