{"id":"https://openalex.org/W7130316647","doi":"https://doi.org/10.1109/tencon66050.2025.11375174","title":"Machine Learning-Based Analysis Method for Brain Activity Measurement Data Under Pleasant and Unpleasant Stimuli","display_name":"Machine Learning-Based Analysis Method for Brain Activity Measurement Data Under Pleasant and Unpleasant Stimuli","publication_year":2025,"publication_date":"2025-10-27","ids":{"openalex":"https://openalex.org/W7130316647","doi":"https://doi.org/10.1109/tencon66050.2025.11375174"},"language":null,"primary_location":{"id":"doi:10.1109/tencon66050.2025.11375174","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon66050.2025.11375174","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2025 - 2025 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5089834596","display_name":"Takumi Ishimoto","orcid":null},"institutions":[{"id":"https://openalex.org/I158123994","display_name":"Toyo University","ror":"https://ror.org/059d6yn51","country_code":"JP","type":"education","lineage":["https://openalex.org/I158123994"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takumi ISHIMOTO","raw_affiliation_strings":["Toyo University,Faculty of Life Science,Asaka-city,Saitama,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toyo University,Faculty of Life Science,Asaka-city,Saitama,Japan","institution_ids":["https://openalex.org/I158123994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108290411","display_name":"Rui Takahashi","orcid":null},"institutions":[{"id":"https://openalex.org/I158123994","display_name":"Toyo University","ror":"https://ror.org/059d6yn51","country_code":"JP","type":"education","lineage":["https://openalex.org/I158123994"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Rui TAKAHASHI","raw_affiliation_strings":["Toyo University,Faculty of Life Science,Asaka-city,Saitama,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toyo University,Faculty of Life Science,Asaka-city,Saitama,Japan","institution_ids":["https://openalex.org/I158123994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029911797","display_name":"Shuya Shida","orcid":"https://orcid.org/0000-0002-6573-5935"},"institutions":[{"id":"https://openalex.org/I158123994","display_name":"Toyo University","ror":"https://ror.org/059d6yn51","country_code":"JP","type":"education","lineage":["https://openalex.org/I158123994"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shuya SHIDA","raw_affiliation_strings":["Toyo University,Faculty of Life Science,Asaka-city,Saitama,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toyo University,Faculty of Life Science,Asaka-city,Saitama,Japan","institution_ids":["https://openalex.org/I158123994"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126352638","display_name":"Yutaka SUZUKI","orcid":null},"institutions":[{"id":"https://openalex.org/I158123994","display_name":"Toyo University","ror":"https://ror.org/059d6yn51","country_code":"JP","type":"education","lineage":["https://openalex.org/I158123994"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yutaka SUZUKI","raw_affiliation_strings":["Toyo University,Faculty of Life Science,Asaka-city,Saitama,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Toyo University,Faculty of Life Science,Asaka-city,Saitama,Japan","institution_ids":["https://openalex.org/I158123994"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I158123994"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.7561894,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1783","last_page":"1787"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","score":0.8995000123977661,"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"}},"topics":[{"id":"https://openalex.org/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","score":0.8995000123977661,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.04670000076293945,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.010300000198185444,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/brain-activity-and-meditation","display_name":"Brain activity and meditation","score":0.6926000118255615},{"id":"https://openalex.org/keywords/neuroimaging","display_name":"Neuroimaging","score":0.5537999868392944},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5011000037193298},{"id":"https://openalex.org/keywords/functional-near-infrared-spectroscopy","display_name":"Functional near-infrared spectroscopy","score":0.4864000082015991},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.48399999737739563},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.4837999939918518},{"id":"https://openalex.org/keywords/stimulus","display_name":"Stimulus (psychology)","score":0.45820000767707825},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4255000054836273},{"id":"https://openalex.org/keywords/prefrontal-cortex","display_name":"Prefrontal cortex","score":0.38940000534057617}],"concepts":[{"id":"https://openalex.org/C120843803","wikidata":"https://www.wikidata.org/wiki/Q4955807","display_name":"Brain activity and meditation","level":3,"score":0.6926000118255615},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.5537999868392944},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5393999814987183},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5170999765396118},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5011000037193298},{"id":"https://openalex.org/C130796691","wikidata":"https://www.wikidata.org/wiki/Q750537","display_name":"Functional near-infrared spectroscopy","level":4,"score":0.4864000082015991},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.48399999737739563},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.4837999939918518},{"id":"https://openalex.org/C2779918689","wikidata":"https://www.wikidata.org/wiki/Q3771842","display_name":"Stimulus (psychology)","level":2,"score":0.45820000767707825},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4255000054836273},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3903000056743622},{"id":"https://openalex.org/C2781195155","wikidata":"https://www.wikidata.org/wiki/Q18680","display_name":"Prefrontal cortex","level":3,"score":0.38940000534057617},{"id":"https://openalex.org/C2910876585","wikidata":"https://www.wikidata.org/wiki/Q43041","display_name":"Deoxygenated Hemoglobin","level":3,"score":0.3675000071525574},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3626999855041504},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.34769999980926514},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.3221000134944916},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.30799999833106995},{"id":"https://openalex.org/C2777670902","wikidata":"https://www.wikidata.org/wiki/Q492038","display_name":"Human brain","level":2,"score":0.29840001463890076},{"id":"https://openalex.org/C50231774","wikidata":"https://www.wikidata.org/wiki/Q639842","display_name":"Brain mapping","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C23677625","wikidata":"https://www.wikidata.org/wiki/Q1428943","display_name":"Psychophysiology","level":2,"score":0.28450000286102295},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C2779345533","wikidata":"https://www.wikidata.org/wiki/Q75785","display_name":"Visual cortex","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2761000096797943},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.2759999930858612},{"id":"https://openalex.org/C558461103","wikidata":"https://www.wikidata.org/wiki/Q154430","display_name":"Anxiety","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C157767197","wikidata":"https://www.wikidata.org/wiki/Q886843","display_name":"Cerebral blood flow","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C2779246727","wikidata":"https://www.wikidata.org/wiki/Q184215","display_name":"Thalamus","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon66050.2025.11375174","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon66050.2025.11375174","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2025 - 2025 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1977754471","https://openalex.org/W2053963261","https://openalex.org/W2095649738","https://openalex.org/W2144724767","https://openalex.org/W2162010696","https://openalex.org/W2164699598","https://openalex.org/W2167101736","https://openalex.org/W2167557160","https://openalex.org/W4388706412","https://openalex.org/W4403394004"],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1],"study,":[2],"we":[3,128,141],"investigated":[4],"the":[5,13,51,101,108,119,159,200,210],"feasibility":[6],"of":[7,37,64,85,184,212],"automatic":[8],"emotion":[9,71,174,229],"classification":[10,177],"by":[11,41],"applying":[12],"machine":[14,133,215],"learning":[15,134,216],"algorithm":[16],"Random":[17,164],"Forest":[18,165],"to":[19,122,136,145,166,173,199],"time-series":[20],"brain":[21,169],"activity":[22],"data":[23],"measured":[24],"using":[25,113,187],"functional":[26],"near-infrared":[27],"spectroscopy":[28],"(fNIRS).":[29],"fNIRS":[30,115,120,213],"is":[31,217],"a":[32,180,218],"noninvasive":[33,226],"neuroimaging":[34],"technique":[35],"capable":[36],"monitoring":[38],"cerebral":[39],"hemodynamics":[40],"detecting":[42],"changes":[43,103],"in":[44,50,104,107,149,234],"oxygenated":[45],"and":[46,62,88,125,132,153,157,190,214,225,243],"deoxygenated":[47],"hemoglobin":[48,150],"concentrations":[49],"cortical":[52],"surface.":[53],"It":[54],"offers":[55],"practical":[56],"advantages":[57],"such":[58,236],"as":[59,237],"portability,":[60],"safety,":[61],"ease":[63],"use,":[65],"making":[66],"it":[67],"suitable":[68],"for":[69,221,228],"real-world":[70],"research.":[72],"Fifteen":[73],"healthy":[74],"male":[75],"participants":[76],"were":[77,111],"presented":[78],"with":[79,231],"emotionally":[80],"valenced":[81],"visual":[82],"stimuli,":[83],"consisting":[84],"pleasant,":[86],"unpleasant,":[87],"neutral":[89],"images":[90],"that":[91,209],"had":[92],"been":[93],"pre-classified":[94],"based":[95],"on":[96],"previous":[97],"subjective":[98],"ratings.":[99],"During":[100],"task,":[102],"blood":[105],"flow":[106],"prefrontal":[109],"cortex":[110],"recorded":[112],"22":[114],"channels.":[116,205],"After":[117],"preprocessing":[118],"signals":[121],"reduce":[123],"drift":[124],"physiological":[126],"noise,":[127],"applied":[129],"statistical":[130],"analyses":[131],"techniques":[135],"evaluate":[137],"emotional":[138],"responses.":[139],"Specifically,":[140],"conducted":[142],"paired":[143],"t-tests":[144],"assess":[146],"significant":[147],"differences":[148],"levels":[151],"before":[152],"during":[154],"stimulus":[155],"presentation,":[156],"used":[158],"feature":[160],"importance":[161],"metric":[162],"from":[163],"identify":[167],"which":[168],"regions":[170],"contributed":[171],"most":[172,203],"classification.":[175],"The":[176],"model":[178],"achieved":[179],"remarkably":[181],"high":[182],"accuracy":[183],"99.48":[185],"%":[186],"all":[188],"channels":[189],"maintained":[191],"strong":[192],"performance":[193],"(96.04":[194],"%)":[195],"even":[196],"when":[197],"restricted":[198],"top":[201],"five":[202],"informative":[204],"These":[206],"results":[207],"indicate":[208],"integration":[211],"promising":[219],"approach":[220],"developing":[222],"objective,":[223],"reliable,":[224],"methods":[227],"recognition,":[230],"potential":[232],"applications":[233],"fields":[235],"affective":[238],"computing,":[239],"mental":[240],"health":[241],"assessment,":[242],"brain-computer":[244],"interfaces.":[245]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-02-19T00:00:00"}
