{"id":"https://openalex.org/W7125984271","doi":"https://doi.org/10.1109/smc58881.2025.11342851","title":"WMTMNet: An Automatic Sleep Staging Model Based on Wavelet Convolution and Multimodal Bilinear Pooling","display_name":"WMTMNet: An Automatic Sleep Staging Model Based on Wavelet Convolution and Multimodal Bilinear Pooling","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125984271","doi":"https://doi.org/10.1109/smc58881.2025.11342851"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11342851","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342851","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5124121478","display_name":"Maohui Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maohui Tian","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications,School of Computer Science,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications,School of Computer Science,Chongqing,China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124135544","display_name":"Yin Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yin Tian","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications,School of Life Health Information Science and Engineering,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications,School of Life Health Information Science and Engineering,Chongqing,China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I10535382"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7493","last_page":"7498"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10234","display_name":"Obstructive Sleep Apnea Research","score":0.45159998536109924,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"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/T10234","display_name":"Obstructive Sleep Apnea Research","score":0.45159998536109924,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"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":0.3147999942302704,"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/T10316","display_name":"Sleep and related disorders","score":0.06199999898672104,"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/interpretability","display_name":"Interpretability","score":0.6561999917030334},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4115999937057495},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.39590001106262207},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.38269999623298645},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.34529998898506165},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33629998564720154},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.3262999951839447},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.31520000100135803}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6832000017166138},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6561999917030334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6302000284194946},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4449000060558319},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4115999937057495},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.39590001106262207},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.38269999623298645},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.34529998898506165},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33629998564720154},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.31520000100135803},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.31349998712539673},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.303600013256073},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.3021000027656555},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2992999851703644},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2946000099182129},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.2888000011444092},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27399998903274536},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C2910364982","wikidata":"https://www.wikidata.org/wiki/Q35831","display_name":"Sleep Stages","level":4,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11342851","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11342851","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7543038129806519,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321135","display_name":"Chongqing University","ror":"https://ror.org/023rhb549"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1545241942","https://openalex.org/W2085426858","https://openalex.org/W2163462953","https://openalex.org/W2604096629","https://openalex.org/W2963150162","https://openalex.org/W2963409068","https://openalex.org/W3128870381","https://openalex.org/W3159541278","https://openalex.org/W3165396901","https://openalex.org/W4312736633","https://openalex.org/W4386208027","https://openalex.org/W4391854859","https://openalex.org/W4398187707","https://openalex.org/W4400525694","https://openalex.org/W4401326911","https://openalex.org/W4402389150"],"related_works":[],"abstract_inverted_index":{"Sleep":[0],"staging":[1],"is":[2,42,90,130,147],"a":[3,73,127,142],"critical":[4],"component":[5],"of":[6,25,34,81,117],"sleep":[7,67,86],"assessment":[8],"and":[9,37,113],"holds":[10],"significant":[11],"value":[12],"for":[13,66],"disease":[14],"diagnosis.":[15],"Although":[16],"existing":[17],"research":[18],"has":[19],"made":[20],"notable":[21],"progress":[22],"in":[23,31,45,84,102],"terms":[24],"performance,":[26],"there":[27],"are":[28],"still":[29],"shortcomings":[30],"the":[32,85,94,115,118,134,138,164],"interpretability":[33],"algorithmic":[35],"decision-making":[36],"outcomes.":[38],"This":[39,88],"\"black-box\"":[40],"issue":[41],"particularly":[43],"concerning":[44],"high-risk":[46],"applications":[47],"such":[48],"as":[49],"medical":[50],"decision-making.":[51],"Therefore,":[52],"this":[53],"paper":[54],"proposes":[55],"an":[56],"interpretable":[57],"hybrid":[58],"deep":[59],"learning":[60],"model":[61,133,167],"that":[62],"incorporates":[63],"expert":[64,179],"knowledge":[65],"stage":[68],"classification.":[69],"First,":[70],"we":[71,106],"employ":[72],"Morlet":[74],"wavelet-based":[75],"kernel":[76],"layer":[77,89],"to":[78,111,122,132,149],"separate":[79],"features":[80,151],"different":[82,123,153],"frequencies":[83],"data.":[87],"designed":[91],"based":[92],"on":[93],"visual":[95],"analysis":[96],"principles":[97],"used":[98],"by":[99],"human":[100],"experts":[101],"polysomnography(PSG)":[103],"recordings.":[104],"Next,":[105],"utilize":[107],"Multi-Scale":[108],"Group":[109],"Convolution(MSGC)":[110],"extract":[112],"reduce":[114],"dimensionality":[116],"time":[119,139],"series":[120],"corresponding":[121],"frequency":[124],"bands.":[125],"Subsequently,":[126],"Transformer":[128],"encoder":[129],"applied":[131],"contextual":[135],"information":[136],"within":[137],"series.":[140],"Finally,":[141],"multimodal":[143],"bilinear":[144],"pooling":[145],"method":[146],"adopted":[148],"fuse":[150],"from":[152],"modalities,":[154],"enabling":[155],"effective":[156],"interaction":[157],"between":[158],"modalities.":[159],"Compared":[160],"with":[161,178],"previous":[162],"studies,":[163],"proposed":[165],"end-to-end":[166],"not":[168],"only":[169],"demonstrates":[170],"excellent":[171],"performance":[172],"but":[173],"also":[174],"provides":[175],"visualizations":[176],"aligned":[177],"knowledge,":[180],"thereby":[181],"enhancing":[182],"interpretability.":[183]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-29T00:00:00"}