{"id":"https://openalex.org/W7160324011","doi":"https://doi.org/10.48550/arxiv.2605.00973","title":"Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning","display_name":"Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning","publication_year":2026,"publication_date":"2026-05-01","ids":{"openalex":"https://openalex.org/W7160324011","doi":"https://doi.org/10.48550/arxiv.2605.00973"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.00973","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.00973","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.00973","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135396760","display_name":"Hao Zhou","orcid":"https://orcid.org/0000-0001-8739-8389"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123527333","display_name":"Simon A. Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Simon A.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135306045","display_name":"Cyrus Tanade","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tanade, Cyrus","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010350636","display_name":"Keum San Chun","orcid":"https://orcid.org/0000-0001-5695-5816"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chun, Keum San","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135406262","display_name":"Juhyeon Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Juhyeon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015173367","display_name":"Migyeong Gwak","orcid":"https://orcid.org/0000-0003-1226-0451"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gwak, Migyeong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092998035","display_name":"Megha Thukral","orcid":"https://orcid.org/0009-0001-5800-5205"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thukral, Megha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135359772","display_name":"Justin Sung","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sung, Justin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064918550","display_name":"Eugene Hwang","orcid":"https://orcid.org/0000-0001-7901-3258"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hwang, Eugene","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123460637","display_name":"Mehrab Bin Morshed","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Morshed, Mehrab Bin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135324872","display_name":"Li Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043961038","display_name":"Viswam Nathan","orcid":"https://orcid.org/0000-0001-8694-8721"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nathan, Viswam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135363772","display_name":"Md Mahbubur Rahman","orcid":"https://orcid.org/0000-0002-2830-1206"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rahman, Md Mahbubur","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113320006","display_name":"Subramaniam Venkatraman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Venkatraman, Subramaniam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5068959441","display_name":"Sharanya Arcot Desai","orcid":"https://orcid.org/0000-0003-4542-6905"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Desai, Sharanya Arcot","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":15,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.2563000023365021,"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":0.2563000023365021,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.18029999732971191,"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.17720000445842743,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/biosignal","display_name":"Biosignal","score":0.949400007724762},{"id":"https://openalex.org/keywords/photoplethysmogram","display_name":"Photoplethysmogram","score":0.6090999841690063},{"id":"https://openalex.org/keywords/phonocardiogram","display_name":"Phonocardiogram","score":0.5724999904632568},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5175999999046326},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4668000042438507},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4657999873161316},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36239999532699585},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.3555999994277954},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.3357999920845032}],"concepts":[{"id":"https://openalex.org/C2779055241","wikidata":"https://www.wikidata.org/wiki/Q644240","display_name":"Biosignal","level":3,"score":0.949400007724762},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6917999982833862},{"id":"https://openalex.org/C116390426","wikidata":"https://www.wikidata.org/wiki/Q7187885","display_name":"Photoplethysmogram","level":3,"score":0.6090999841690063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6083999872207642},{"id":"https://openalex.org/C159693508","wikidata":"https://www.wikidata.org/wiki/Q3301075","display_name":"Phonocardiogram","level":2,"score":0.5724999904632568},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5175999999046326},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4814000129699707},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4668000042438507},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4657999873161316},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36239999532699585},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3555999994277954},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3467000126838684},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.32420000433921814},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C2778858076","wikidata":"https://www.wikidata.org/wiki/Q5249539","display_name":"Decodes","level":3,"score":0.26489999890327454},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2639999985694885},{"id":"https://openalex.org/C2780167933","wikidata":"https://www.wikidata.org/wiki/Q1550652","display_name":"Pulse (music)","level":3,"score":0.2632000148296356},{"id":"https://openalex.org/C2779435589","wikidata":"https://www.wikidata.org/wiki/Q967103","display_name":"Heart sounds","level":2,"score":0.25220000743865967},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2515999972820282},{"id":"https://openalex.org/C39300077","wikidata":"https://www.wikidata.org/wiki/Q9530","display_name":"Breathing","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.00973","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.00973","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.00973","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.00973","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Biosignals":[0],"acquired":[1],"from":[2],"different":[3,182],"locations":[4],"on":[5,122],"the":[6,14,33,44,51,62,104,154,162,170],"body":[7,145],"often":[8],"provide":[9],"temporally":[10,89],"ordered":[11,90],"views":[12],"of":[13,124,172,184],"same":[15],"underlying":[16,187],"physiological":[17],"process.":[18,188],"However,":[19],"most":[20],"existing":[21],"self":[22],"supervised":[23],"learning":[24],"methods":[25],"treat":[26],"these":[27],"signals":[28,180],"as":[29,92],"interchangeable":[30],"views,":[31],"overlooking":[32],"directional":[34],"temporal":[35,174],"dynamics":[36],"that":[37,82,109,115,153],"link":[38],"them.":[39],"A":[40],"canonical":[41],"example":[42],"is":[43,159,190],"relationship":[45],"between":[46],"electrocardiography":[47],"(ECG),":[48],"which":[49,60],"captures":[50],"electrical":[52],"activation":[53],"initiating":[54],"each":[55],"heartbeat,":[56],"and":[57,119,138,147],"photoplethysmography":[58],"(PPG),":[59],"records":[61],"resulting":[63],"peripheral":[64],"pulse":[65],"delayed":[66],"by":[67],"vascular":[68],"dynamics.":[69],"To":[70],"capture":[71],"this":[72],"structured":[73],"relationship,":[74],"we":[75],"introduce":[76],"xMAE,":[77],"a":[78,93,185],"biosignal":[79],"pretraining":[80,110,178],"framework":[81],"leverages":[83],"masked":[84],"cross":[85],"modal":[86],"reconstruction":[87],"across":[88,143],"biosignals":[91],"training":[94],"time":[95],"constraint":[96],"to":[97],"encourage":[98],"physiologically":[99],"meaningful":[100],"timing":[101,157],"structure":[102,158,175],"in":[103,161],"learned":[105,163],"representations.":[106,165],"We":[107],"show":[108],"with":[111],"xMAE":[112,168],"yields":[113],"representations":[114],"outperform":[116],"both":[117],"unimodal":[118],"multimodal":[120,177],"baselines":[121],"15":[123],"19":[125],"downstream":[126],"tasks,":[127],"including":[128],"cardiovascular":[129],"outcome":[130],"prediction,":[131],"abnormal":[132],"laboratory":[133],"test":[134],"detection,":[135],"sleep":[136],"staging,":[137],"demographic":[139],"inference,":[140],"while":[141],"generalizing":[142],"devices,":[144],"locations,":[146],"acquisition":[148],"settings.":[149],"Further":[150],"analysis":[151],"suggests":[152],"ECG":[155],"PPG":[156,164],"reflected":[160],"More":[166],"broadly,":[167],"demonstrates":[169],"effectiveness":[171],"incorporating":[173],"into":[176],"when":[179],"observe":[181],"stages":[183],"shared":[186],"Code":[189],"available":[191],"at":[192],"https://github.com/hzhou3/xMAE.":[193]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-06T00:00:00"}
