{"id":"https://openalex.org/W3042216344","doi":"https://doi.org/10.1109/memea49120.2020.9137218","title":"A Deep Learning Approach for Mood Recognition from Wearable Data","display_name":"A Deep Learning Approach for Mood Recognition from Wearable Data","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3042216344","doi":"https://doi.org/10.1109/memea49120.2020.9137218","mag":"3042216344"},"language":"en","primary_location":{"id":"doi:10.1109/memea49120.2020.9137218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea49120.2020.9137218","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","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/A5087960213","display_name":"Giuseppe Romano Tizzano","orcid":null},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giuseppe Romano Tizzano","raw_affiliation_strings":["Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Naples, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Naples, Italy","institution_ids":["https://openalex.org/I71267560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036322916","display_name":"Matteo Spezialetti","orcid":"https://orcid.org/0000-0001-5786-3999"},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Matteo Spezialetti","raw_affiliation_strings":["Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Naples, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Naples, Italy","institution_ids":["https://openalex.org/I71267560"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046630253","display_name":"Silvia Rossi","orcid":"https://orcid.org/0000-0002-3379-1756"},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Silvia Rossi","raw_affiliation_strings":["Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Naples, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Naples, Italy","institution_ids":["https://openalex.org/I71267560"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9669,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.86437886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9991000294685364,"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/T11519","display_name":"Digital Mental Health Interventions","score":0.982200026512146,"subfield":{"id":"https://openalex.org/subfields/3202","display_name":"Applied Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7752565145492554},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7731741666793823},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7069700360298157},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6397982835769653},{"id":"https://openalex.org/keywords/mood","display_name":"Mood","score":0.5554851293563843},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5395376682281494},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5368784666061401},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.502234935760498},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.48840779066085815},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.456925630569458},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.43575942516326904}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7752565145492554},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7731741666793823},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7069700360298157},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6397982835769653},{"id":"https://openalex.org/C2780733359","wikidata":"https://www.wikidata.org/wiki/Q331769","display_name":"Mood","level":2,"score":0.5554851293563843},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5395376682281494},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5368784666061401},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.502234935760498},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.48840779066085815},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.456925630569458},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.43575942516326904},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/memea49120.2020.9137218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea49120.2020.9137218","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2007041320","https://openalex.org/W2081420711","https://openalex.org/W2134122539","https://openalex.org/W2152423878","https://openalex.org/W2170784062","https://openalex.org/W2235060430","https://openalex.org/W2338224285","https://openalex.org/W2753251847","https://openalex.org/W2785802062","https://openalex.org/W2810625036","https://openalex.org/W2902014068","https://openalex.org/W2986108748","https://openalex.org/W3106223685","https://openalex.org/W3160237479","https://openalex.org/W6793723330","https://openalex.org/W7020981078"],"related_works":["https://openalex.org/W4206357785","https://openalex.org/W4281381188","https://openalex.org/W3192840557","https://openalex.org/W2951211570","https://openalex.org/W4375928479","https://openalex.org/W3167935049","https://openalex.org/W3023427754","https://openalex.org/W3131673289","https://openalex.org/W4393011546","https://openalex.org/W3198847674"],"abstract_inverted_index":{"Emotion":[0],"and":[1,26,31,36,54,65,141,159,172,185,233],"mood":[2,38,48,62,129],"recognition":[3,130],"plays":[4],"a":[5,46,70,98,104,124,132,138,253],"key":[6],"role":[7],"in":[8,12,96,163,173,248],"human-robot":[9],"interaction,":[10],"especially":[11,227],"the":[13,50,58,61,90,146,198,206,212,218,250],"context":[14],"of":[15,52,60,101,117,148,200,214,252],"socially":[16],"assistive":[17],"robotics.":[18],"Mood-aware":[19],"robots":[20],"could":[21],"be":[22,108],"useful":[23],"as":[24,157,160,230],"companions":[25],"social":[27],"assistants":[28],"for":[29,43,128],"elders":[30],"people":[32],"affected":[33],"by":[34],"depression":[35],"other":[37,91],"disorders.":[39],"An":[40],"interesting":[41],"option":[42],"continuously":[44],"tracking":[45],"user's":[47],"is":[49,68],"use":[51,147,213],"wearable":[53],"mobile":[55],"devices.":[56],"However,":[57,237],"classification":[59,80,219],"from":[63,103,131],"physiological":[64],"kinematics":[66],"data":[67,102,202],"still":[69],"challenge,":[71],"due":[72],"to":[73,107,196,204,223],"intersubjects":[74],"differences:":[75],"on":[76,89],"one":[77],"hand,":[78,92],"\"one-fits-all\"":[79],"approaches":[81],"usually":[82],"achieve":[83,245],"lower":[84],"accuracy":[85,220],"than":[86],"person-specific":[87],"methods;":[88],"personalized":[93,254],"models":[94,188],"require":[95],"general":[97],"large":[99],"amount":[100,199],"single":[105],"subject":[106],"trained":[109],"and,":[110],"therefore,":[111],"becomes":[112],"effective":[113],"after":[114],"long":[115],"periods":[116],"acquisition.":[118],"In":[119],"this":[120],"paper,":[121],"we":[122,238],"propose":[123,145],"deep":[125],"learning":[126,178,194,225,242],"approach":[127],"publicly":[133],"available":[134],"dataset":[135],"that":[136,211,240],"includes":[137],"gyroscope,":[139],"accelerometer,":[140],"heart-rate":[142],"data.":[143],"We":[144,166,190],"long-short":[149],"term":[150],"memory":[151],"networks":[152],"(LSTM),":[153],"testing":[154],"them":[155],"both":[156,170],"classifiers":[158],"features":[161],"extractors":[162,232],"hybrid":[164],"models.":[165],"compared":[167],"their":[168],"performances":[169],"against":[171],"conjunction":[174],"with":[175,221,235],"traditional":[176],"machine":[177,224],"approaches,":[179,226],"namely":[180],"support":[181],"vector":[182],"machines":[183],"(SVM)":[184],"Gaussian":[186],"mixture":[187],"(GMM).":[189],"also":[191],"consider":[192],"transfer":[193,241],"strategies":[195],"reduce":[197],"personal":[201],"needed":[203],"train":[205],"model.":[207,255],"Our":[208],"results":[209,247],"show":[210],"LSTMs":[215],"significantly":[216],"improves":[217],"respect":[222],"if":[228],"employed":[229],"feature":[231],"combined":[234],"SVM.":[236],"observed":[239],"does":[243],"not":[244],"significant":[246],"boosting":[249],"training":[251]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":8}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}