{"id":"https://openalex.org/W4390992204","doi":"https://doi.org/10.1109/bibm58861.2023.10385549","title":"Exploring Early Stress Detection from Multimodal Time Series with Deep Reinforcement Learning","display_name":"Exploring Early Stress Detection from Multimodal Time Series with Deep Reinforcement Learning","publication_year":2023,"publication_date":"2023-12-05","ids":{"openalex":"https://openalex.org/W4390992204","doi":"https://doi.org/10.1109/bibm58861.2023.10385549"},"language":"en","primary_location":{"id":"doi:10.1109/bibm58861.2023.10385549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5108312635","display_name":"Leonardo Furia","orcid":null},"institutions":[{"id":"https://openalex.org/I155125353","display_name":"Universit\u00e0 Campus Bio-Medico","ror":"https://ror.org/04gqx4x78","country_code":"IT","type":"education","lineage":["https://openalex.org/I155125353"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Leonardo Furia","raw_affiliation_strings":["University Campus Bio-Medico of Rome,Unit of Computer Systems & Bioinformatics,Department of Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University Campus Bio-Medico of Rome,Unit of Computer Systems & Bioinformatics,Department of Engineering","institution_ids":["https://openalex.org/I155125353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076081587","display_name":"Matteo Tortora","orcid":"https://orcid.org/0000-0002-3932-7380"},"institutions":[{"id":"https://openalex.org/I155125353","display_name":"Universit\u00e0 Campus Bio-Medico","ror":"https://ror.org/04gqx4x78","country_code":"IT","type":"education","lineage":["https://openalex.org/I155125353"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Matteo Tortora","raw_affiliation_strings":["University Campus Bio-Medico of Rome,Unit of Computer Systems & Bioinformatics,Department of Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University Campus Bio-Medico of Rome,Unit of Computer Systems & Bioinformatics,Department of Engineering","institution_ids":["https://openalex.org/I155125353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003216983","display_name":"Paolo Soda","orcid":"https://orcid.org/0000-0003-2621-072X"},"institutions":[{"id":"https://openalex.org/I155125353","display_name":"Universit\u00e0 Campus Bio-Medico","ror":"https://ror.org/04gqx4x78","country_code":"IT","type":"education","lineage":["https://openalex.org/I155125353"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Soda","raw_affiliation_strings":["University Campus Bio-Medico of Rome,Unit of Computer Systems & Bioinformatics,Department of Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University Campus Bio-Medico of Rome,Unit of Computer Systems & Bioinformatics,Department of Engineering","institution_ids":["https://openalex.org/I155125353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023365911","display_name":"Rosa Sicilia","orcid":"https://orcid.org/0000-0002-2513-0827"},"institutions":[{"id":"https://openalex.org/I155125353","display_name":"Universit\u00e0 Campus Bio-Medico","ror":"https://ror.org/04gqx4x78","country_code":"IT","type":"education","lineage":["https://openalex.org/I155125353"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Rosa Sicilia","raw_affiliation_strings":["University Campus Bio-Medico of Rome,Unit of Computer Systems & Bioinformatics,Department of Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University Campus Bio-Medico of Rome,Unit of Computer Systems & Bioinformatics,Department of Engineering","institution_ids":["https://openalex.org/I155125353"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I155125353"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1917","last_page":"1920"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.982699990272522,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.982699990272522,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9509000182151794,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9223999977111816,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/reinforcement-learning","display_name":"Reinforcement learning","score":0.6703771352767944},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6347290277481079},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6082471013069153},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6045047044754028},{"id":"https://openalex.org/keywords/stress","display_name":"Stress (linguistics)","score":0.5311046242713928},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.48528358340263367},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4332486093044281},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.43194055557250977}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6703771352767944},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6347290277481079},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6082471013069153},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6045047044754028},{"id":"https://openalex.org/C21036866","wikidata":"https://www.wikidata.org/wiki/Q181767","display_name":"Stress (linguistics)","level":2,"score":0.5311046242713928},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.48528358340263367},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4332486093044281},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.43194055557250977},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bibm58861.2023.10385549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.unige.it:11567/1230859","is_oa":false,"landing_page_url":"https://hdl.handle.net/11567/1230859","pdf_url":null,"source":{"id":"https://openalex.org/S4377196291","display_name":"CINECA IRIS Institutial Research Information System (University of Genoa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I83816512","host_organization_name":"University of Genoa","host_organization_lineage":["https://openalex.org/I83816512"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2209383581","https://openalex.org/W2563752936","https://openalex.org/W2902760701","https://openalex.org/W2918153055","https://openalex.org/W3098982663","https://openalex.org/W3131167370","https://openalex.org/W3167394498","https://openalex.org/W4313342895","https://openalex.org/W4317761548","https://openalex.org/W4362641063","https://openalex.org/W6688249303","https://openalex.org/W6747473740"],"related_works":["https://openalex.org/W4306904969","https://openalex.org/W2138720691","https://openalex.org/W4362501864","https://openalex.org/W4380318855","https://openalex.org/W2031695474","https://openalex.org/W2024136090","https://openalex.org/W4391331176","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"In":[0],"our":[1],"fast-paced":[2],"world,":[3],"timely":[4],"access":[5],"to":[6,41,66],"information":[7],"is":[8,12,93],"essential.":[9],"This":[10,37],"urgency":[11],"highlighted":[13],"in":[14,87],"stress":[15,29,53,88],"detection,":[16],"where":[17],"swift":[18],"actions":[19],"can":[20],"mitigate":[21],"harmful":[22],"psycho-physiological":[23],"effects.":[24],"We":[25,55],"introduce":[26],"an":[27],"early":[28],"detection":[30],"method":[31,38],"using":[32,79],"Deep":[33],"Reinforcement":[34],"Learning":[35],"(DRL).":[36],"utilizes":[39],"DRL":[40,64],"efficiently":[42],"analyze":[43],"time":[44],"series":[45],"data":[46,70],"segments,":[47],"aiming":[48],"for":[49],"accurate":[50],"and":[51],"quick":[52],"classification.":[54],"employ":[56],"a":[57,76,80],"dynamic":[58],"observation":[59],"window":[60],"strategy,":[61],"allowing":[62],"the":[63],"agent":[65],"adjust":[67],"based":[68],"on":[69,75],"complexity.":[71],"Our":[72],"evaluations,":[73],"performed":[74],"public":[77],"dataset":[78],"Leave-One-Subject-Out":[81],"(LOSO)":[82],"method,":[83],"emphasize":[84],"DRL\u2019s":[85],"potential":[86],"detection.":[89],"The":[90],"related":[91],"code":[92],"available":[94],"at":[95],"https://github.com/cosbidev/DRL-4-Early-Stress-Detection.":[96]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2024-01-19T00:00:00"}