{"id":"https://openalex.org/W2966429875","doi":"https://doi.org/10.1109/bsn.2019.8771075","title":"A Deep Learning Approach on Gender and Age Recognition using a Single Inertial Sensor","display_name":"A Deep Learning Approach on Gender and Age Recognition using a Single Inertial Sensor","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W2966429875","doi":"https://doi.org/10.1109/bsn.2019.8771075","mag":"2966429875"},"language":"en","primary_location":{"id":"doi:10.1109/bsn.2019.8771075","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bsn.2019.8771075","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 16th International Conference on Wearable and Implantable 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/A5059787157","display_name":"Yingnan Sun","orcid":"https://orcid.org/0000-0002-8566-8055"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Yingnan Sun","raw_affiliation_strings":["Dept. of Computing, Imperial College London, London, UK"],"affiliations":[{"raw_affiliation_string":"Dept. of Computing, Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021505567","display_name":"Frank P.-W. Lo","orcid":"https://orcid.org/0000-0002-0358-6567"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Frank P.-W. Lo","raw_affiliation_strings":["The Hamlyn Center, Imperial College London, London, UK"],"affiliations":[{"raw_affiliation_string":"The Hamlyn Center, Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063187094","display_name":"Benny Lo","orcid":"https://orcid.org/0000-0002-5080-108X"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Benny Lo","raw_affiliation_strings":["The Hamlyn Center, Imperial College London, London, UK"],"affiliations":[{"raw_affiliation_string":"The Hamlyn Center, Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5059787157"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":1.3283,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.84639949,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"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/T11448","display_name":"Face recognition and analysis","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9955000281333923,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9800000190734863,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6001496911048889},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5528775453567505},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4807124435901642},{"id":"https://openalex.org/keywords/inertial-frame-of-reference","display_name":"Inertial frame of reference","score":0.4505508542060852},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3398364186286926}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6001496911048889},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5528775453567505},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4807124435901642},{"id":"https://openalex.org/C173386949","wikidata":"https://www.wikidata.org/wiki/Q192735","display_name":"Inertial frame of reference","level":2,"score":0.4505508542060852},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3398364186286926},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bsn.2019.8771075","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bsn.2019.8771075","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 16th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","raw_type":"proceedings-article"},{"id":"pmh:oai:spiral.imperial.ac.uk:10044/1/75191","is_oa":false,"landing_page_url":"http://hdl.handle.net/10044/1/75191","pdf_url":null,"source":{"id":"https://openalex.org/S4306401396","display_name":"Spiral (Imperial College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I47508984","host_organization_name":"Imperial College London","host_organization_lineage":["https://openalex.org/I47508984"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE 16th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5099999904632568,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G4314500828","display_name":null,"funder_award_id":"EP/N02334X/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1002857674","https://openalex.org/W1522301498","https://openalex.org/W1545140005","https://openalex.org/W1561897670","https://openalex.org/W1965804146","https://openalex.org/W2018110376","https://openalex.org/W2027576351","https://openalex.org/W2096101171","https://openalex.org/W2102742858","https://openalex.org/W2137604415","https://openalex.org/W2155041972","https://openalex.org/W2218097338","https://openalex.org/W2470715095","https://openalex.org/W2620878397","https://openalex.org/W2763913564","https://openalex.org/W2767040310","https://openalex.org/W2964121744","https://openalex.org/W3104966193","https://openalex.org/W6683113847"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407"],"abstract_inverted_index":{"Extracting":[0],"human":[1],"attributes,":[2],"such":[3,27],"as":[4,28],"gender":[5,42,118],"and":[6,18,31,43,78,93,114,116,124,128],"age,":[7],"from":[8,69],"biometrics":[9],"have":[10],"received":[11],"much":[12],"attention":[13],"in":[14],"recent":[15],"years.":[16],"Gender":[17],"age":[19,44,111],"recognition":[20,45],"can":[21,101],"provide":[22],"crucial":[23],"information":[24],"for":[25,108,126],"applications":[26],"security,":[29],"healthcare,":[30],"gaming.":[32],"In":[33],"this":[34],"paper,":[35],"a":[36,47],"novel":[37],"deep":[38],"learning":[39],"approach":[40,55,100],"on":[41],"using":[46,58],"single":[48],"inertial":[49,62],"sensors":[50],"is":[51,56],"proposed.":[52],"The":[53],"proposed":[54,82,99],"tested":[57],"the":[59,76,81,94,98],"largest":[60],"available":[61],"sensor-based":[63],"gait":[64],"database":[65],"with":[66,119],"data":[67],"collected":[68],"more":[70],"than":[71],"700":[72],"subjects.":[73],"To":[74],"demonstrate":[75],"robustness":[77],"effectiveness":[79],"of":[80,86,106,122],"approach,":[83],"10":[84],"trials":[85],"inter-subject":[87],"Monte-Carlo":[88],"cross":[89],"validation":[90],"were":[91],"conducted,":[92],"results":[95],"show":[96],"that":[97],"achieve":[102],"an":[103],"averaged":[104,120],"accuracy":[105],"86.6%\u00b12.4%":[107],"distinguishing":[109],"two":[110],"groups:":[112],"teen":[113],"adult,":[115],"recognizing":[117],"accuracies":[121],"88.6%\u00b12.5%":[123],"73.9%\u00b12.8%":[125],"adults":[127],"teens":[129],"respectively.":[130]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}