{"id":"https://openalex.org/W7204229832","doi":"https://doi.org/10.3390/s26175401","title":"DSGF-Net: A Lightweight Dual-Stream Gated Fusion Network for Cross-Subject fNIRS Motor Task Classification","display_name":"DSGF-Net: A Lightweight Dual-Stream Gated Fusion Network for Cross-Subject fNIRS Motor Task Classification","publication_year":2026,"publication_date":"2026-08-26","ids":{"openalex":"https://openalex.org/W7204229832","doi":"https://doi.org/10.3390/s26175401","pmid":"https://pubmed.ncbi.nlm.nih.gov/42740021"},"language":"en","primary_location":{"id":"doi:10.3390/s26175401","doi":"https://doi.org/10.3390/s26175401","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s26175401","pdf_url":null,"source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/s26175401","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5146750671","display_name":"Jingfu Wu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I15062923","display_name":"Tianjin Normal University","ror":"https://ror.org/05x2td559","country_code":"CN","type":"education","lineage":["https://openalex.org/I15062923"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingfu Wu","raw_affiliation_strings":["College of Artificial Intelligence, Tianjin Normal University, Tianjin 300387, China","Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin 300387, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, Tianjin Normal University, Tianjin 300387, China","institution_ids":["https://openalex.org/I15062923"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin 300387, China","institution_ids":["https://openalex.org/I15062923"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148232176","display_name":"Xiu Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I15062923","display_name":"Tianjin Normal University","ror":"https://ror.org/05x2td559","country_code":"CN","type":"education","lineage":["https://openalex.org/I15062923"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiu Zhang","raw_affiliation_strings":["College of Artificial Intelligence, Tianjin Normal University, Tianjin 300387, China","Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin 300387, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, Tianjin Normal University, Tianjin 300387, China","institution_ids":["https://openalex.org/I15062923"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin 300387, China","institution_ids":["https://openalex.org/I15062923"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148232176","display_name":"Xiu Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I15062923","display_name":"Tianjin Normal University","ror":"https://ror.org/05x2td559","country_code":"CN","type":"education","lineage":["https://openalex.org/I15062923"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiu Zhang","raw_affiliation_strings":["College of Artificial Intelligence, Tianjin Normal University, Tianjin 300387, China","Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin 300387, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, Tianjin Normal University, Tianjin 300387, China","institution_ids":["https://openalex.org/I15062923"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin 300387, China","institution_ids":["https://openalex.org/I15062923"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148199261","display_name":"Xin Zhang","orcid":"https://orcid.org/0000-0003-3846-5498","observed_orcids":["https://orcid.org/0000-0003-3846-5498"]},"institutions":[{"id":"https://openalex.org/I15062923","display_name":"Tianjin Normal University","ror":"https://ror.org/05x2td559","country_code":"CN","type":"education","lineage":["https://openalex.org/I15062923"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Zhang","raw_affiliation_strings":["College of Artificial Intelligence, Tianjin Normal University, Tianjin 300387, China","Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin 300387, China"],"raw_orcid":"https://orcid.org/0000-0003-3846-5498","affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, Tianjin Normal University, Tianjin 300387, China","institution_ids":["https://openalex.org/I15062923"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin 300387, China","institution_ids":["https://openalex.org/I15062923"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5148199261","display_name":"Xin Zhang","orcid":"https://orcid.org/0000-0003-3846-5498","observed_orcids":["https://orcid.org/0000-0003-3846-5498"]},"institutions":[{"id":"https://openalex.org/I15062923","display_name":"Tianjin Normal University","ror":"https://ror.org/05x2td559","country_code":"CN","type":"education","lineage":["https://openalex.org/I15062923"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Zhang","raw_affiliation_strings":["College of Artificial Intelligence, Tianjin Normal University, Tianjin 300387, China","Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin 300387, China"],"raw_orcid":"https://orcid.org/0000-0003-3846-5498","affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, Tianjin Normal University, Tianjin 300387, China","institution_ids":["https://openalex.org/I15062923"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin 300387, China","institution_ids":["https://openalex.org/I15062923"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5146710190","display_name":"Deping Huang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I15062923","display_name":"Tianjin Normal University","ror":"https://ror.org/05x2td559","country_code":"CN","type":"education","lineage":["https://openalex.org/I15062923"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Deping Huang","raw_affiliation_strings":["College of Artificial Intelligence, Tianjin Normal University, Tianjin 300387, China","Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin 300387, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, Tianjin Normal University, Tianjin 300387, China","institution_ids":["https://openalex.org/I15062923"]},{"raw_affiliation_string":"Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin 300387, China","institution_ids":["https://openalex.org/I15062923"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5148199261","https://openalex.org/A5148232176"],"corresponding_institution_ids":["https://openalex.org/I15062923"],"apc_list":{"value":2600,"currency":"CHF","value_usd":3137},"apc_paid":{"value":2600,"currency":"CHF","value_usd":3137},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.67096774,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"26","issue":"17","first_page":"5401","last_page":"5401"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9312000274658203,"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":0.9312000274658203,"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":0.035100001841783524,"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/T10784","display_name":"Muscle activation and electromyography studies","score":0.002300000051036477,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/functional-near-infrared-spectroscopy","display_name":"functional near-infrared spectroscopy","score":0.8230000138282776},{"id":"https://openalex.org/keywords/motor-imagery","display_name":"motor imagery","score":0.7559999823570251},{"id":"https://openalex.org/keywords/brain-computer-interface","display_name":"brain-computer interface","score":0.9079999923706055},{"id":"https://openalex.org/keywords/cross-subject-classification","display_name":"cross-subject classification","score":0.9110000133514404},{"id":"https://openalex.org/keywords/two-stream-network","display_name":"two-stream network","score":0.6050000190734863},{"id":"https://openalex.org/keywords/gated-feature-fusion","display_name":"gated feature fusion","score":0.8199999928474426},{"id":"https://openalex.org/keywords/inter-individual-variability","display_name":"interindividual variability","score":0.7419999837875366},{"id":"https://openalex.org/keywords/lightweight-deep-learning-models","display_name":"lightweight deep learning","score":0.8009999990463257}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7936999797821045},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7566999793052673},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6712999939918518},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5626000165939331},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.5412999987602234},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5238000154495239},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.515500009059906},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.4706999957561493},{"id":"https://openalex.org/C54808283","wikidata":"https://www.wikidata.org/wiki/Q6918191","display_name":"Motor imagery","level":4,"score":0.4514999985694885},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4424000084400177},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4415000081062317},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.42489999532699585},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.41100001335144043},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.3797000050544739},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.3747999966144562},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.36980000138282776},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.3652999997138977},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.35519999265670776},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.350600004196167},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3434999883174896},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3151000142097473},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3102000057697296},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.3059000074863434},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2937999963760376},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.2768999934196472},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.258899986743927},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.2558000087738037},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.25099998712539673}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019265","descriptor_name":"Spectroscopy, Near-Infrared","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D019265","descriptor_name":"Spectroscopy, Near-Infrared","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D062207","descriptor_name":"Brain-Computer Interfaces","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D062207","descriptor_name":"Brain-Computer Interfaces","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.3390/s26175401","doi":"https://doi.org/10.3390/s26175401","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s26175401","pdf_url":null,"source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:42740021","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42740021","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,"listed_in":[],"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":"Sensors (Basel, Switzerland)","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13568332","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13568332/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13568332/pdf/sensors-26-05401.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,"listed_in":[],"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":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:786eefbf2ce6479a9bafef8ea943d963","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/786eefbf2ce6479a9bafef8ea943d963","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,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 26, Iss 17, p 5401 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s26175401","doi":"https://doi.org/10.3390/s26175401","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s26175401","pdf_url":null,"source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.46810001134872437,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"sustainable_development_goals_aurora":[{"score":0.691510021686554,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2045561515","https://openalex.org/W2087461551","https://openalex.org/W2337310062","https://openalex.org/W2552578398","https://openalex.org/W2559463885","https://openalex.org/W2886301707","https://openalex.org/W2963844898","https://openalex.org/W2984132992","https://openalex.org/W2994384968","https://openalex.org/W3007780430","https://openalex.org/W3037312461","https://openalex.org/W3062839060","https://openalex.org/W3112960229","https://openalex.org/W3120824653","https://openalex.org/W3137666915","https://openalex.org/W3142672147","https://openalex.org/W3195460166","https://openalex.org/W3200600885","https://openalex.org/W3200930171","https://openalex.org/W3202503690","https://openalex.org/W4205386513","https://openalex.org/W4388469973","https://openalex.org/W4390874259","https://openalex.org/W4408585589","https://openalex.org/W4414341893","https://openalex.org/W4414957113"],"related_works":[],"abstract_inverted_index":{"Functional":[0],"near-infrared":[1],"spectroscopy":[2],"(fNIRS)":[3],"has":[4],"become":[5],"an":[6,232],"important":[7],"signal":[8,253],"source":[9],"in":[10,247],"motor":[11,241],"imagery":[12],"(MI)":[13],"brain-computer":[14],"interface":[15],"research":[16],"due":[17],"to":[18,73,119,200],"its":[19],"non-invasive":[20],"nature":[21],"and":[22,39,43,50,150,174,195,227,251],"high":[23],"application":[24],"flexibility.":[25],"However,":[26],"fNIRS":[27,79],"signals":[28,106],"exhibit":[29],"significant":[30],"inter-subject":[31],"variability,":[32],"complementary":[33,75],"information":[34],"from":[35,107],"oxygenated":[36],"hemoglobin":[37,41],"(HbO)":[38],"deoxygenated":[40],"(HbR),":[42],"complex":[44],"spatiotemporal":[45],"dynamics,":[46],"making":[47],"their":[48],"efficient":[49],"robust":[51],"classification":[52,171,212],"challenging.":[53],"To":[54],"address":[55],"these":[56],"issues,":[57],"this":[58,111],"paper":[59],"proposes":[60],"a":[61,70,113,178,216,222],"Dual-Stream":[62],"Gated":[63],"Fusion":[64],"Network":[65],"(DSGF-Net).":[66],"This":[67],"model":[68],"employs":[69],"dual-branch":[71,193],"architecture":[72],"perform":[74],"feature":[76,126,134],"modeling":[77],"of":[78,97,124,131,141,181,191],"signals:":[80],"one":[81],"branch":[82],"focuses":[83],"on":[84,155],"extracting":[85],"multi-scale":[86],"temporal":[87],"dynamic":[88],"features,":[89],"while":[90,214],"the":[91,94,105,122,129,132,138,142,161,189,192,196],"other":[92],"learns":[93],"spatial":[95],"distribution":[96],"hemodynamic":[98],"features":[99],"across":[100,167],"channels,":[101],"thereby":[102,136],"effectively":[103],"characterizing":[104],"different":[108,125,184],"perspectives.":[109],"Upon":[110],"foundation,":[112],"gated":[114,197],"fusion":[115,130,198],"mechanism":[116,199],"was":[117],"designed":[118],"adaptively":[120],"adjust":[121],"importance":[123],"dimensions":[127],"after":[128],"two":[133,146],"streams,":[135],"enhancing":[137],"discriminative":[139],"power":[140],"fused":[143],"representation.":[144],"On":[145],"public":[147],"datasets,":[148],"MI":[149],"UFFT,":[151],"experimental":[152],"results":[153,206],"based":[154],"leave-one-subject-out":[156],"(LOSO)":[157],"cross-validation":[158],"show":[159,207],"that":[160,208],"proposed":[162],"method":[163],"achieves":[164,210],"competitive":[165],"performance":[166,182,201,213,226],"metrics":[168],"such":[169],"as":[170],"accuracy,":[172],"F1-score,":[173],"Kappa":[175],"coefficient.":[176],"Furthermore,":[177,203],"comparative":[179],"analysis":[180,205],"under":[183],"network":[185],"component":[186],"configurations":[187],"validates":[188],"contributions":[190],"structure":[194],"improvements.":[202],"complexity":[204],"DSGF-Net":[209,230],"superior":[211],"maintaining":[215],"relatively":[217],"small":[218],"parameter":[219],"size,":[220],"striking":[221],"good":[223],"balance":[224],"between":[225],"computational":[228],"complexity.":[229],"provides":[231],"effective,":[233],"lightweight":[234],"deep":[235],"learning":[236],"framework":[237],"for":[238],"offline":[239],"fNIRS-based":[240],"task":[242],"classification,":[243],"with":[244],"potential":[245],"applications":[246],"cross-subject":[248],"BCI":[249],"systems":[250],"brain":[252],"decoding.":[254]},"counts_by_year":[],"updated_date":"2026-10-15T10:00:46.086208","created_date":"2026-08-27T00:00:00"}