{"id":"https://openalex.org/W4415707630","doi":"https://doi.org/10.1109/tce.2025.3627222","title":"An Ordinal Pattern Similarity-Guided Supervised Prototype Contrastive Learning Framework With Enhanced Token Selection Module for Sleep Apnea Detection Based on Wearable PPG Bracelet","display_name":"An Ordinal Pattern Similarity-Guided Supervised Prototype Contrastive Learning Framework With Enhanced Token Selection Module for Sleep Apnea Detection Based on Wearable PPG Bracelet","publication_year":2025,"publication_date":"2025-10-30","ids":{"openalex":"https://openalex.org/W4415707630","doi":"https://doi.org/10.1109/tce.2025.3627222"},"language":null,"primary_location":{"id":"doi:10.1109/tce.2025.3627222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2025.3627222","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Consumer Electronics","raw_type":"journal-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/A5056048018","display_name":"Weiyan Qiu","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weiyan Qiu","raw_affiliation_strings":["School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhuo Chen","orcid":"https://orcid.org/0009-0009-5387-4645"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuo Chen","raw_affiliation_strings":["School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0009-5387-4645","affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049672707","display_name":"Yanxun Lu","orcid":"https://orcid.org/0009-0003-5414-6531"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanxun Lu","raw_affiliation_strings":["School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0003-5414-6531","affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100427145","display_name":"Changhong Wang","orcid":"https://orcid.org/0000-0003-2821-9357"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changhong Wang","raw_affiliation_strings":["School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-2821-9357","affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102851337","display_name":"Guanzheng Liu","orcid":"https://orcid.org/0000-0002-1208-7479"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanzheng Liu","raw_affiliation_strings":["School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-1208-7479","affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5056048018"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37859701,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"71","issue":"4","first_page":"9820","last_page":"9831"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10234","display_name":"Obstructive Sleep Apnea Research","score":0.9650999903678894,"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":0.9650999903678894,"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.0034000000450760126,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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":0.0027000000700354576,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.6262999773025513},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.501800000667572},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4805000126361847},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4702000021934509},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.46970000863075256},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.45730000734329224},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4171999990940094},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.39989998936653137},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.3952000141143799}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7290999889373779},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.6262999773025513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5996999740600586},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.501800000667572},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4805000126361847},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4702000021934509},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.46970000863075256},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.45730000734329224},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4480000138282776},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4171999990940094},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.39989998936653137},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3952000141143799},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.37689998745918274},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.3598000109195709},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3377000093460083},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.33469998836517334},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3253999948501587},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.3228999972343445},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.3167000114917755},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3102000057697296},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.29490000009536743},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2930999994277954},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2750000059604645},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25380000472068787},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tce.2025.3627222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2025.3627222","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Consumer Electronics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2012373480","https://openalex.org/W2014683958","https://openalex.org/W2026191693","https://openalex.org/W2087978863","https://openalex.org/W2105132636","https://openalex.org/W2108180331","https://openalex.org/W2137822036","https://openalex.org/W2164179736","https://openalex.org/W2170860662","https://openalex.org/W2291427785","https://openalex.org/W2773952774","https://openalex.org/W3048664285","https://openalex.org/W3093887727","https://openalex.org/W3110690419","https://openalex.org/W4200394775","https://openalex.org/W4206038815","https://openalex.org/W4214634256","https://openalex.org/W4226134417","https://openalex.org/W4281725377","https://openalex.org/W4288801241","https://openalex.org/W4289538117","https://openalex.org/W4294830572","https://openalex.org/W4297095249","https://openalex.org/W4310074863","https://openalex.org/W4312866014","https://openalex.org/W4313316760","https://openalex.org/W4313893670","https://openalex.org/W4360584328","https://openalex.org/W4385573172","https://openalex.org/W4386640254","https://openalex.org/W4388895071","https://openalex.org/W4392022764","https://openalex.org/W4400230327","https://openalex.org/W4402714520","https://openalex.org/W4403039281","https://openalex.org/W4406435601"],"related_works":[],"abstract_inverted_index":{"Sleep":[0],"apnea":[1],"(SA)":[2],"is":[3,242],"a":[4,74,160,186],"chronic":[5],"condition":[6],"with":[7,57],"wide-ranging":[8],"effects,":[9],"yet":[10],"screening":[11],"remains":[12],"limited.":[13],"SA":[14,108,120,191,238],"detection":[15,31,192],"using":[16],"wearable":[17,170],"smart":[18],"wristband":[19],"devices":[20],"has":[21],"the":[22,64,68,89,102,112,117,123,169,174,205,217],"potential":[23,235],"to":[24,92,129,151,210],"significantly":[25],"improve":[26],"this":[27,43,86],"situation.":[28],"However,":[29],"existing":[30],"methods":[32],"suffer":[33],"from":[34],"limited":[35],"representation":[36],"capacity":[37],"and":[38,146,155,164,185],"achieve":[39],"low":[40],"sensitivity.":[41],"To":[42],"end,":[44],"we":[45,72,132,198],"propose":[46],"an":[47,134],"ordinal":[48],"pattern":[49],"similarity-guided":[50],"supervised":[51],"prototype":[52],"contrastive":[53],"learning":[54],"(ops-spcl)":[55],"framework":[56],"enhanced":[58],"token":[59,69,98],"selection":[60,70],"module.":[61],"Specifically,":[62],"in":[63,107,122,179],"self-attention":[65],"mechanism":[66],"of":[67,83,104,114,119,127,208,219],"module,":[71],"integrate":[73],"selective":[75],"kernel":[76],"convolution-ReLU":[77],"operation.":[78],"By":[79,189],"incorporating":[80],"receptive":[81],"fields":[82],"varying":[84],"scales,":[85],"approach":[87,232],"enhances":[88],"model\u2019s":[90],"ability":[91],"focus":[93],"more":[94,161],"precisely":[95],"on":[96,204],"target-relevant":[97],"features,":[99],"thereby":[100],"improving":[101],"capture":[103],"temporal":[105],"dependencies":[106],"events.":[109],"Furthermore,":[110],"considering":[111],"challenges":[113],"accurately":[115],"capturing":[116],"features":[118],"events":[121],"peak-to-peak":[124],"interval":[125],"sequences":[126],"mild":[128,209],"moderate":[130,211],"patients,":[131],"design":[133],"ops-spcl":[135],"loss":[136],"function.":[137],"This":[138],"function":[139],"explicitly":[140],"constructs":[141],"hard":[142,206],"negative":[143],"sample":[144,149],"pairs":[145,150],"easy":[147],"positive":[148],"enhance":[152],"intra-class":[153],"compactness":[154],"inter-class":[156],"separability":[157],"that":[158,200,230],"generates":[159],"refined,":[162],"effective,":[163],"discriminative":[165],"feature":[166],"space.":[167],"On":[168],"bracelet":[171],"PPG":[172],"dataset,":[173],"proposed":[175],"model":[176],"performs":[177],"well":[178],"per-segment":[180],"detection,":[181],"achieving":[182],"72.4%":[183],"sensitivity":[184],"0.687":[187],"F1-score.":[188],"analyzing":[190],"rates":[193],"across":[194,224],"different":[195],"population":[196],"groups,":[197],"demonstrate":[199],"it":[201],"effectively":[202],"focuses":[203],"samples":[207],"patients.":[212],"Moreover,":[213],"these":[214],"findings":[215],"highlight":[216],"generality":[218],"its":[220],"strong":[221],"generalization":[222],"capabilities":[223],"multiple":[225],"datasets.":[226],"These":[227],"results":[228],"suggest":[229],"our":[231],"holds":[233],"significant":[234],"for":[236],"large-scale":[237],"detection.":[239],"Our":[240],"code":[241],"publicly":[243],"available.":[244]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-30T00:00:00"}
