{"id":"https://openalex.org/W7162100116","doi":"https://doi.org/10.1109/percom67906.2026.11524561","title":"Attention Feature Fusion with Cluster Contrastive Learning for Snoring and Breath-Holding Detection Using Seismic Sensing","display_name":"Attention Feature Fusion with Cluster Contrastive Learning for Snoring and Breath-Holding Detection Using Seismic Sensing","publication_year":2026,"publication_date":"2026-03-16","ids":{"openalex":"https://openalex.org/W7162100116","doi":"https://doi.org/10.1109/percom67906.2026.11524561"},"language":null,"primary_location":{"id":"doi:10.1109/percom67906.2026.11524561","is_oa":false,"landing_page_url":"https://doi.org/10.1109/percom67906.2026.11524561","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE International Conference on Pervasive Computing and Communications (PerCom)","raw_type":"proceedings-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/A5102909478","display_name":"Yingjian Song","orcid":"https://orcid.org/0009-0005-5601-4465"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yingjian Song","raw_affiliation_strings":["University of Georgia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136806112","display_name":"Jiayu Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiayu Chen","raw_affiliation_strings":["University of Georgia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044289321","display_name":"Zixuan Zeng","orcid":"https://orcid.org/0009-0005-7051-7421"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zixuan Zeng","raw_affiliation_strings":["University of Georgia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136735377","display_name":"Yida Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yida Zhang","raw_affiliation_strings":["University of Georgia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034544067","display_name":"Zaid Farooq Pitafi","orcid":"https://orcid.org/0009-0004-0126-9244"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zaid Farooq Pitafi","raw_affiliation_strings":["University of Georgia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136793386","display_name":"Bradley G. Phillips","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bradley G. Phillips","raw_affiliation_strings":["University of Georgia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136763187","display_name":"xiang zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiang Zhang","raw_affiliation_strings":["University of Georgia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136789965","display_name":"Fei Dou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fei Dou","raw_affiliation_strings":["University of Georgia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101993988","display_name":"Wenli Song","orcid":"https://orcid.org/0000-0001-8174-1772"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenzhan Song","raw_affiliation_strings":["University of Georgia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"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":0.7690604,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.20640000700950623,"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"}},"topics":[{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.20640000700950623,"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"}},{"id":"https://openalex.org/T10234","display_name":"Obstructive Sleep Apnea Research","score":0.1915999948978424,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.08129999786615372,"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/feature","display_name":"Feature (linguistics)","score":0.5339000225067139},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5123000144958496},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.4011000096797943},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.33340001106262207},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.32269999384880066},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3203999996185303}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6848999857902527},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5730999708175659},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5339000225067139},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5123000144958496},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.4011000096797943},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.33340001106262207},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.32269999384880066},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3203999996185303},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.296099990606308},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2870999872684479},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.2818000018596649},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.26739999651908875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/percom67906.2026.11524561","is_oa":false,"landing_page_url":"https://doi.org/10.1109/percom67906.2026.11524561","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE International Conference on Pervasive Computing and Communications (PerCom)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5577867031097412,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W2017475793","https://openalex.org/W2067925997","https://openalex.org/W2069763158","https://openalex.org/W2085522395","https://openalex.org/W2088356001","https://openalex.org/W2132271223","https://openalex.org/W2515118094","https://openalex.org/W2609758525","https://openalex.org/W2750410834","https://openalex.org/W2752782242","https://openalex.org/W2785563066","https://openalex.org/W2792112256","https://openalex.org/W2802665251","https://openalex.org/W2806548613","https://openalex.org/W2889059709","https://openalex.org/W2912654414","https://openalex.org/W2972301465","https://openalex.org/W3003063577","https://openalex.org/W3143898587","https://openalex.org/W3173286189","https://openalex.org/W3190152617","https://openalex.org/W3199148273","https://openalex.org/W4212859008","https://openalex.org/W4289550913","https://openalex.org/W4289752563","https://openalex.org/W4306250089","https://openalex.org/W4385245566","https://openalex.org/W4385565385","https://openalex.org/W4386126974","https://openalex.org/W4386223259","https://openalex.org/W4386825072","https://openalex.org/W4389775185","https://openalex.org/W4402349535","https://openalex.org/W4403408022","https://openalex.org/W4404034561","https://openalex.org/W4406036771","https://openalex.org/W4406793961","https://openalex.org/W4408980599","https://openalex.org/W4411403361","https://openalex.org/W4414067788","https://openalex.org/W4416926468"],"related_works":[],"abstract_inverted_index":{"Snoring":[0,71],"and":[1,46,51,62,82,97,107,118,127,134,140,143,179,191,197,209],"breath-stopping":[2,52,81,86,208],"are":[3,194],"key":[4],"symptoms":[5],"of":[6,99,177,183],"sleep":[7],"apnea.":[8],"Most":[9],"existing":[10],"studies":[11],"primarily":[12],"focus":[13],"on":[14,169],"wearable":[15],"devices":[16,21],"or":[17,33],"smartphone-based":[18,26],"systems.":[19],"Wearable":[20],"can":[22,102],"be":[23],"uncomfortable,":[24],"while":[25],"systems":[27],"often":[28],"require":[29],"specific":[30],"angles,":[31],"distances,":[32],"positions,":[34],"making":[35],"them":[36],"sensitive":[37],"to":[38,122],"environmental":[39],"changes.":[40],"This":[41],"paper":[42],"proposes":[43],"a":[44,55,76,90],"contactless":[45],"engagement-free":[47],"system":[48,160,163,205],"for":[49,148,187],"snoring":[50],"detection":[53],"using":[54],"seismic":[56],"sensor.":[57],"Distinguishing":[58],"between":[59],"snoring,":[60,190],"breath-stopping,":[61,189],"normal":[63,83,192],"breathing":[64,193],"from":[65,125,137],"raw":[66,100],"data":[67,101],"alone":[68],"is":[69],"challenging.":[70],"features":[72,87,104,136],"typically":[73],"reside":[74],"in":[75,89,105,156],"higher":[77],"frequency":[78,92],"range":[79],"than":[80],"breathing,":[84],"with":[85],"appearing":[88],"lower":[91],"range.":[93],"Calculating":[94],"the":[95,138],"differential":[96,126,139],"integral":[98,128,141],"enhance":[103],"low":[106],"high":[108],"frequencies,":[109],"respectively.":[110,199],"We":[111],"introduce":[112],"AFFCL,":[113],"an":[114,145,174,180],"attention":[115,146],"feature":[116,149],"fusion":[117],"contrastive":[119,154],"learning":[120,155],"framework":[121],"leverage":[123],"information":[124],"signals.":[129],"AFFCL":[130,157],"generates":[131],"both":[132],"shared":[133],"exclusive":[135],"signals":[142],"employs":[144],"mechanism":[147],"fusion.":[150],"Additionally,":[151],"cluster-level":[152],"supervised":[153],"further":[158],"enhances":[159],"performance.":[161],"Our":[162],"has":[164],"been":[165],"performed":[166],"5-fold":[167],"cross-validation":[168],"44":[170],"people,":[171],"which":[172],"achieves":[173],"average":[175],"accuracy":[176,186],"93.40%":[178],"F1":[181],"score":[182],"92.42%.":[184],"The":[185],"detecting":[188],"89.54%,":[195],"94.60%,":[196],"96.06%,":[198],"Evaluation":[200],"results":[201],"demonstrate":[202],"that":[203],"our":[204],"effectively":[206],"identifies":[207],"snoring.":[210]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-23T00:00:00"}
