{"id":"https://openalex.org/W4405271389","doi":"https://doi.org/10.1109/bsn63547.2024.10780702","title":"Attention-Based Explainable AI for Wearable Multivariate Data: A Case Study on Affect Status Prediction","display_name":"Attention-Based Explainable AI for Wearable Multivariate Data: A Case Study on Affect Status Prediction","publication_year":2024,"publication_date":"2024-10-15","ids":{"openalex":"https://openalex.org/W4405271389","doi":"https://doi.org/10.1109/bsn63547.2024.10780702"},"language":"en","primary_location":{"id":"doi:10.1109/bsn63547.2024.10780702","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bsn63547.2024.10780702","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 20th International Conference on Body Sensor Networks (BSN)","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/A5101826614","display_name":"Yuning Wang","orcid":"https://orcid.org/0000-0001-7351-6866"},"institutions":[{"id":"https://openalex.org/I155660961","display_name":"University of Turku","ror":"https://ror.org/05vghhr25","country_code":"FI","type":"education","lineage":["https://openalex.org/I155660961"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Yuning Wang","raw_affiliation_strings":["University of Turku,Department of Computing,Turku,Finland"],"affiliations":[{"raw_affiliation_string":"University of Turku,Department of Computing,Turku,Finland","institution_ids":["https://openalex.org/I155660961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013382897","display_name":"Zhongqi Yang","orcid":"https://orcid.org/0000-0002-4196-0652"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhongqi Yang","raw_affiliation_strings":["University of California,Department of Computer Science,Irvine,California,USA"],"affiliations":[{"raw_affiliation_string":"University of California,Department of Computer Science,Irvine,California,USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084047638","display_name":"Iman Azimi","orcid":"https://orcid.org/0000-0001-5003-299X"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Iman Azimi","raw_affiliation_strings":["University of California,Department of Computer Science,Irvine,California,USA"],"affiliations":[{"raw_affiliation_string":"University of California,Department of Computer Science,Irvine,California,USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042140592","display_name":"Amir M. Rahmani","orcid":"https://orcid.org/0000-0003-0725-1155"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amir M. Rahmani","raw_affiliation_strings":["University of California,Department of Computer Science,Irvine,California,USA"],"affiliations":[{"raw_affiliation_string":"University of California,Department of Computer Science,Irvine,California,USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019546150","display_name":"Pasi Liljeberg","orcid":"https://orcid.org/0000-0002-9392-3589"},"institutions":[{"id":"https://openalex.org/I155660961","display_name":"University of Turku","ror":"https://ror.org/05vghhr25","country_code":"FI","type":"education","lineage":["https://openalex.org/I155660961"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Pasi Liljeberg","raw_affiliation_strings":["University of Turku,Department of Computing,Turku,Finland"],"affiliations":[{"raw_affiliation_string":"University of Turku,Department of Computing,Turku,Finland","institution_ids":["https://openalex.org/I155660961"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101826614"],"corresponding_institution_ids":["https://openalex.org/I155660961"],"apc_list":null,"apc_paid":null,"fwci":0.533,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.72916459,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.9742000102996826,"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"}},"topics":[{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.9742000102996826,"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"}},{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.9380000233650208,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.7804004549980164},{"id":"https://openalex.org/keywords/affect","display_name":"Affect (linguistics)","score":0.7609264254570007},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.7145735621452332},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6867956519126892},{"id":"https://openalex.org/keywords/multivariate-analysis","display_name":"Multivariate analysis","score":0.5889660120010376},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5839943289756775},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47827231884002686},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.15843483805656433}],"concepts":[{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.7804004549980164},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.7609264254570007},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.7145735621452332},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6867956519126892},{"id":"https://openalex.org/C38180746","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate analysis","level":2,"score":0.5889660120010376},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5839943289756775},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47827231884002686},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.15843483805656433},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bsn63547.2024.10780702","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bsn63547.2024.10780702","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 20th International Conference on Body Sensor Networks (BSN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1990785877","https://openalex.org/W2148905283","https://openalex.org/W2322248124","https://openalex.org/W2949449669","https://openalex.org/W3122022143","https://openalex.org/W3188872815","https://openalex.org/W4200023943","https://openalex.org/W4229003689","https://openalex.org/W4285340930","https://openalex.org/W4312373350","https://openalex.org/W4385245566","https://openalex.org/W4386727350","https://openalex.org/W4389230857","https://openalex.org/W4392362441","https://openalex.org/W4393237312","https://openalex.org/W6766978945","https://openalex.org/W6787926458","https://openalex.org/W6802566335","https://openalex.org/W6846348810"],"related_works":["https://openalex.org/W2406638334","https://openalex.org/W40745829","https://openalex.org/W4318262572","https://openalex.org/W1978357124","https://openalex.org/W1578824628","https://openalex.org/W2032728545","https://openalex.org/W1570805059","https://openalex.org/W4250754046","https://openalex.org/W4243682621","https://openalex.org/W2036849593"],"abstract_inverted_index":{"Wearable":[0],"technology":[1],"enables":[2],"ubiquitous":[3],"health":[4],"monitoring":[5],"where":[6],"multivariate":[7,18],"physiological":[8],"and":[9,45,56,66,86,99,108,117,151,156,175,197],"behavioral":[10],"data":[11,22,40,89],"can":[12],"be":[13],"captured":[14],"over":[15,141],"time.":[16],"Such":[17],"time":[19],"series":[20],"(MTS)":[21],"in":[23,60,72,201],"healthcare":[24,202],"applications":[25],"needs":[26],"technique":[27],"to":[28,52,84,104],"interpret":[29,87],"the":[30,54,64,115,189],"analysis":[31,41],"results.":[32],"However,":[33],"existing":[34],"deep":[35],"learning":[36],"models":[37,147],"for":[38,148,173,177,195],"MTS":[39,88,199],"often":[42],"lack":[43],"interpretability,":[44],"current":[46],"explainable":[47],"AI":[48],"(xAI)":[49],"techniques":[50],"fail":[51],"capture":[53,105],"temporal":[55,107,116],"inter-variable":[57,109],"complexities":[58],"inherent":[59],"MTS.":[61],"This":[62],"hinders":[63],"trust":[65],"integration":[67],"of":[68,183,191],"these":[69],"AI-based":[70],"systems":[71],"clinical":[73],"decision-making.":[74],"In":[75],"this":[76],"paper,":[77],"we":[78],"propose":[79],"an":[80],"attention-based":[81],"xAI":[82,193],"method":[83,123,165,194],"classify":[85],"collected":[90,133],"from":[91,134],"wearable":[92,139],"devices.":[93],"Our":[94,164],"approach":[95],"leverages":[96],"self-attention":[97],"mechanisms":[98],"graph":[100],"attention":[101],"layers":[102],"(GAT)":[103],"both":[106,114],"dependencies,":[110],"providing":[111],"interpretability":[112],"at":[113],"modality":[118],"levels.":[119],"We":[120,144],"evaluate":[121],"our":[122,192],"using":[124],"a":[125,161],"longitudinal":[126],"affect":[127,153],"status":[128],"monitoring.":[129],"The":[130],"dataset":[131],"was":[132],"21":[135],"college":[136],"students":[137],"via":[138],"devices":[140],"one":[142],"year.":[143],"train":[145],"separate":[146],"positive":[149],"(PA)":[150],"negative":[152],"(NA)":[154],"prediction,":[155],"compare":[157],"their":[158],"performance":[159],"with":[160,170],"Transformer-based":[162],"method.":[163],"achieves":[166],"robust":[167],"classification":[168,200],"performance,":[169],"78.62%":[171],"accuracy":[172],"PA":[174],"76.30%":[176],"NA,":[178],"while":[179],"offering":[180],"transparent":[181],"explanations":[182],"its":[184],"decisions.":[185],"These":[186],"findings":[187],"highlight":[188],"potential":[190],"reliable":[196],"interpretable":[198],"applications.":[203]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
