{"id":"https://openalex.org/W3044651858","doi":"https://doi.org/10.1109/access.2020.3010715","title":"Deep Neural Networks for Human Activity Recognition With Wearable Sensors: Leave-One-Subject-Out Cross-Validation for Model Selection","display_name":"Deep Neural Networks for Human Activity Recognition With Wearable Sensors: Leave-One-Subject-Out Cross-Validation for Model Selection","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3044651858","doi":"https://doi.org/10.1109/access.2020.3010715","mag":"3044651858"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3010715","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3010715","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09144538.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09144538.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037480186","display_name":"Davoud Gholamiangonabadi","orcid":"https://orcid.org/0000-0002-5476-0959"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Davoud Gholamiangonabadi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Western University, London, Canada"],"raw_orcid":"https://orcid.org/0000-0002-5476-0959","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Western University, London, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062753333","display_name":"Nikita Kiselov","orcid":"https://orcid.org/0000-0003-0297-7811"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Nikita Kiselov","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Western University, London, Canada"],"raw_orcid":"https://orcid.org/0000-0003-0297-7811","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Western University, London, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012962681","display_name":"Katarina Grolinger","orcid":"https://orcid.org/0000-0003-0062-8212"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Katarina Grolinger","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Western University, London, Canada"],"raw_orcid":"https://orcid.org/0000-0003-0062-8212","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Western University, London, Canada","institution_ids":["https://openalex.org/I125749732"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125749732"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":8.3768,"has_fulltext":true,"cited_by_count":191,"citation_normalized_percentile":{"value":0.98463518,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"8","issue":null,"first_page":"133982","last_page":"133994"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9998999834060669,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9998999834060669,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9563000202178955,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8057690858840942},{"id":"https://openalex.org/keywords/cross-validation","display_name":"Cross-validation","score":0.7381595373153687},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7213149070739746},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7162639498710632},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.6681198477745056},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5867094993591309},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.562391996383667},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5610381960868835},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5249255299568176},{"id":"https://openalex.org/keywords/subject","display_name":"Subject (documents)","score":0.46228504180908203},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.4288422763347626},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3860650062561035},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.2798283100128174}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8057690858840942},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.7381595373153687},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7213149070739746},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7162639498710632},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.6681198477745056},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5867094993591309},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.562391996383667},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5610381960868835},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5249255299568176},{"id":"https://openalex.org/C2777855551","wikidata":"https://www.wikidata.org/wiki/Q12310021","display_name":"Subject (documents)","level":2,"score":0.46228504180908203},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.4288422763347626},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3860650062561035},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.2798283100128174},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"id":"https://openalex.org/C161191863","wikidata":"https://www.wikidata.org/wiki/Q199655","display_name":"Library science","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3010715","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3010715","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09144538.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9bea9b3dbf2c4991ab92d75c8c999e3c","is_oa":true,"landing_page_url":"https://doaj.org/article/9bea9b3dbf2c4991ab92d75c8c999e3c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 133982-133994 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3010715","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3010715","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09144538.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.5799999833106995}],"awards":[{"id":"https://openalex.org/G2980479518","display_name":null,"funder_award_id":"RGPIN-2018","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G3879245900","display_name":"Edge-Cloud Computing for Internet of Things Data Analytics","funder_award_id":"rgpin-2018-06222","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"}],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3044651858.pdf","grobid_xml":"https://content.openalex.org/works/W3044651858.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W100883972","https://openalex.org/W123295786","https://openalex.org/W1493204252","https://openalex.org/W1538131130","https://openalex.org/W1581808154","https://openalex.org/W1726370773","https://openalex.org/W1852728451","https://openalex.org/W1857382374","https://openalex.org/W2023302299","https://openalex.org/W2073401630","https://openalex.org/W2078439954","https://openalex.org/W2091066410","https://openalex.org/W2101234009","https://openalex.org/W2116436990","https://openalex.org/W2123277412","https://openalex.org/W2141018395","https://openalex.org/W2163605009","https://openalex.org/W2207642662","https://openalex.org/W2243012843","https://openalex.org/W2288074780","https://openalex.org/W2466829632","https://openalex.org/W2517717368","https://openalex.org/W2551239383","https://openalex.org/W2594035233","https://openalex.org/W2594116048","https://openalex.org/W2600842288","https://openalex.org/W2614259051","https://openalex.org/W2804739511","https://openalex.org/W2805240935","https://openalex.org/W2807963368","https://openalex.org/W2889310761","https://openalex.org/W2891267845","https://openalex.org/W2892279525","https://openalex.org/W2901599055","https://openalex.org/W2907227550","https://openalex.org/W2919115771","https://openalex.org/W2940682483","https://openalex.org/W2945490067","https://openalex.org/W2963855167","https://openalex.org/W2967729586","https://openalex.org/W3006281198","https://openalex.org/W3007028389","https://openalex.org/W3008533347","https://openalex.org/W3100650847","https://openalex.org/W6632100814","https://openalex.org/W6675354045","https://openalex.org/W6684191040","https://openalex.org/W6696429117","https://openalex.org/W6704286305","https://openalex.org/W6726225210","https://openalex.org/W6752381170"],"related_works":["https://openalex.org/W2353818951","https://openalex.org/W4293226380","https://openalex.org/W1605879311","https://openalex.org/W2090763504","https://openalex.org/W2385763735","https://openalex.org/W148178222","https://openalex.org/W2386394344","https://openalex.org/W2382806131","https://openalex.org/W2006683254","https://openalex.org/W2550904580"],"abstract_inverted_index":{"Human":[0],"Activity":[1],"Recognition":[2],"(HAR)":[3],"has":[4],"been":[5,155],"attracting":[6],"significant":[7],"research":[8],"attention":[9],"because":[10],"of":[11,15,126,133,206],"the":[12,50,58,61,80,88,92,117,121,127,134,182,185,199,204,210],"increasing":[13],"availability":[14],"environmental":[16],"and":[17,142,165,173],"wearable":[18],"sensors":[19],"for":[20,79,91,120,136,209],"collecting":[21],"HAR":[22],"data.":[23],"In":[24],"recent":[25],"years,":[26],"deep":[27],"learning":[28,102],"approaches":[29],"have":[30,154],"demonstrated":[31],"a":[32,74,108,170],"great":[33],"success":[34],"due":[35],"to":[36,39,56,68,194],"their":[37],"ability":[38],"model":[40],"complex":[41],"systems.":[42],"However,":[43],"these":[44],"models":[45],"are":[46,77],"often":[47],"evaluated":[48,191,197],"on":[49,87,107],"same":[51,183],"subjects":[52,76,89],"as":[53,148,150],"those":[54],"used":[55,119],"train":[57],"model;":[59],"thus,":[60],"provided":[62],"accuracy":[63,186],"estimates":[64,84],"do":[65],"not":[66],"pertain":[67],"new":[69,109,137],"subjects.":[70,138],"Occasionally,":[71],"one":[72],"or":[73],"few":[75],"selected":[78,90],"evaluation,":[81],"but":[82],"such":[83],"highly":[85],"depend":[86],"evaluation.":[93,211],"Consequently,":[94],"this":[95],"paper":[96],"examines":[97],"how":[98],"well":[99,149],"different":[100],"machine":[101],"architectures":[103,147],"make":[104],"generalizations":[105],"based":[106],"subject(s)":[110],"by":[111,169],"using":[112,207],"Leave-One-Subject-Out":[113],"Cross-Validation":[114],"(LOSOCV).":[115],"Changing":[116],"subject":[118],"evaluation":[122],"in":[123],"each":[124],"fold":[125],"cross-validation,":[128,202],"LOSOCV":[129,193,208],"provides":[130],"subject-independent":[131],"estimate":[132],"performance":[135],"Six":[139],"feed":[140],"forward":[141],"convolutional":[143],"neural":[144],"network":[145],"(CNN)":[146],"four":[151],"pre-processing":[152],"scenarios":[153],"considered.":[156],"Results":[157],"show":[158],"that":[159],"CNN":[160],"architecture":[161],"with":[162,192,198],"two":[163],"convolutions":[164],"one-dimensional":[166],"filter":[167],"accompanied":[168],"sliding":[171],"window":[172],"vector":[174],"magnitude,":[175],"generalizes":[176],"better":[177],"than":[178],"other":[179],"architectures.":[180],"For":[181],"CNN,":[184],"improves":[187],"from":[188],"85.1%":[189],"when":[190,196],"99.85%":[195],"traditional":[200],"10-fold":[201],"demonstrating":[203],"importance":[205]},"counts_by_year":[{"year":2026,"cited_by_count":27},{"year":2025,"cited_by_count":43},{"year":2024,"cited_by_count":34},{"year":2023,"cited_by_count":24},{"year":2022,"cited_by_count":40},{"year":2021,"cited_by_count":21},{"year":2020,"cited_by_count":2}],"updated_date":"2026-08-15T07:11:24.734988","created_date":"2025-10-10T00:00:00"}