{"id":"https://openalex.org/W2914106530","doi":"https://doi.org/10.3390/s19030521","title":"A Comparison of Machine Learning and Deep Learning Techniques for Activity Recognition using Mobile Devices","display_name":"A Comparison of Machine Learning and Deep Learning Techniques for Activity Recognition using Mobile Devices","publication_year":2019,"publication_date":"2019-01-26","ids":{"openalex":"https://openalex.org/W2914106530","doi":"https://doi.org/10.3390/s19030521","mag":"2914106530","pmid":"https://pubmed.ncbi.nlm.nih.gov/30691177"},"language":"en","primary_location":{"id":"doi:10.3390/s19030521","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19030521","pdf_url":"https://www.mdpi.com/1424-8220/19/3/521/pdf?version=1548846453","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/19/3/521/pdf?version=1548846453","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069993099","display_name":"Alejandro Baldominos","orcid":"https://orcid.org/0000-0002-8906-7572"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Alejandro Baldominos","raw_affiliation_strings":["Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain","Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain. abaldomi@inf.uc3m.es"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]},{"raw_affiliation_string":"Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain. abaldomi@inf.uc3m.es","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035508090","display_name":"Alejandro Cervantes","orcid":"https://orcid.org/0000-0001-5442-953X"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Alejandro Cervantes","raw_affiliation_strings":["Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain","Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain. acervant@inf.uc3m.es"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]},{"raw_affiliation_string":"Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain. acervant@inf.uc3m.es","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027117264","display_name":"Yago S\u00e1ez","orcid":"https://orcid.org/0000-0002-0998-2907"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Yago Saez","raw_affiliation_strings":["Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain","Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain. yago.saez@uc3m.es"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]},{"raw_affiliation_string":"Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain. yago.saez@uc3m.es","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114585209","display_name":"Pedro Isasi","orcid":"https://orcid.org/0000-0001-6397-1865"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Pedro Isasi","raw_affiliation_strings":["Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain","Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain. isasi@ia.uc3m.es"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain","institution_ids":["https://openalex.org/I50357001"]},{"raw_affiliation_string":"Department of Computer Science, University Carlos III of Madrid, 28911 Legan\u00e9s, Madrid, Spain. isasi@ia.uc3m.es","institution_ids":["https://openalex.org/I50357001"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5069993099"],"corresponding_institution_ids":["https://openalex.org/I50357001"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":3.7802,"has_fulltext":false,"cited_by_count":72,"citation_normalized_percentile":{"value":0.94703657,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"19","issue":"3","first_page":"521","last_page":"521"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9998000264167786,"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":0.9998000264167786,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9761999845504761,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.957099974155426,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8009869456291199},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7277292609214783},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6796549558639526},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6784784197807312},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6311230659484863},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6166031360626221},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5871210098266602},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.5374852418899536},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5130506753921509},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.5000190734863281},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.4562443792819977},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43317320942878723},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4267529249191284}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8009869456291199},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7277292609214783},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6796549558639526},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6784784197807312},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6311230659484863},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6166031360626221},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5871210098266602},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.5374852418899536},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5130506753921509},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.5000190734863281},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.4562443792819977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43317320942878723},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4267529249191284},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.3390/s19030521","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19030521","pdf_url":"https://www.mdpi.com/1424-8220/19/3/521/pdf?version=1548846453","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:30691177","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30691177","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:dnet:earchivo____::573b89646f8099de91b91c3fe1812631","is_oa":false,"landing_page_url":"http://hdl.handle.net/10016/28165","pdf_url":null,"source":{"id":"https://openalex.org/S4306402641","display_name":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Cient\u00edficas)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4383465926","host_organization_name":"LA Referencia","host_organization_lineage":["https://openalex.org/I4383465926"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:74aa422d7c384abda7625494df1a3c7f","is_oa":true,"landing_page_url":"https://doaj.org/article/74aa422d7c384abda7625494df1a3c7f","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 19, Iss 3, p 521 (2019)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:5384944","is_oa":true,"landing_page_url":"http://europepmc.org/pmc/articles/PMC6386875","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:mdpi.com:/1424-8220/19/3/521/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/s19030521","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:6386875","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6386875","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s19030521","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19030521","pdf_url":"https://www.mdpi.com/1424-8220/19/3/521/pdf?version=1548846453","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.6000000238418579}],"awards":[{"id":"https://openalex.org/G1655995892","display_name":null,"funder_award_id":"GPU Grant Program","funder_id":"https://openalex.org/F4320309480","funder_display_name":"Nvidia"}],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2914106530.pdf","grobid_xml":"https://content.openalex.org/works/W2914106530.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W176323845","https://openalex.org/W1538131130","https://openalex.org/W1665214252","https://openalex.org/W1854498722","https://openalex.org/W1971130285","https://openalex.org/W1996484636","https://openalex.org/W2014601643","https://openalex.org/W2023302299","https://openalex.org/W2026297770","https://openalex.org/W2054242744","https://openalex.org/W2056132907","https://openalex.org/W2064675550","https://openalex.org/W2095705004","https://openalex.org/W2097575504","https://openalex.org/W2098798128","https://openalex.org/W2101234009","https://openalex.org/W2112796928","https://openalex.org/W2118585731","https://openalex.org/W2122111042","https://openalex.org/W2129343065","https://openalex.org/W2129793335","https://openalex.org/W2270470215","https://openalex.org/W2304267454","https://openalex.org/W2404851027","https://openalex.org/W2473781013","https://openalex.org/W2550797816","https://openalex.org/W2732997537","https://openalex.org/W2751594996","https://openalex.org/W2789868604","https://openalex.org/W2790414609","https://openalex.org/W2801908962","https://openalex.org/W2804356137","https://openalex.org/W2911964244","https://openalex.org/W2914106530","https://openalex.org/W3126142534","https://openalex.org/W6674330103","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W2989490741","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642","https://openalex.org/W138569904","https://openalex.org/W2390914021","https://openalex.org/W2389417819"],"abstract_inverted_index":{"We":[0,50,108],"have":[1,109],"compared":[2],"the":[3,28,33,56,117,131,143],"performance":[4],"of":[5,62,89,97],"different":[6],"machine":[7,73],"learning":[8,74,81,135],"techniques":[9],"for":[10,71],"human":[11],"activity":[12,57],"recognition.":[13],"Experiments":[14],"were":[15],"made":[16],"using":[17,90],"a":[18,25,52,60],"benchmark":[19],"dataset":[20,36],"where":[21],"each":[22],"subject":[23],"wore":[24],"device":[26],"in":[27,104],"pocket":[29],"and":[30,47,69,126],"another":[31],"on":[32,85,123,127],"wrist.":[34],"The":[35],"comprises":[37],"thirteen":[38],"activities,":[39,42],"including":[40],"physical":[41],"common":[43],"postures,":[44],"working":[45],"activities":[46],"leisure":[48],"activities.":[49],"apply":[51],"methodology":[53],"known":[54],"as":[55],"recognition":[58],"chain,":[59],"sequence":[61],"steps":[63],"involving":[64],"preprocessing,":[65],"segmentation,":[66],"feature":[67],"extraction":[68],"classification":[70],"traditional":[72],"methods;":[75],"we":[76],"also":[77],"tested":[78,144],"convolutional":[79],"deep":[80],"networks":[82],"that":[83,95,111],"operate":[84],"raw":[86],"data":[87,128],"instead":[88],"computed":[91],"features.":[92],"Results":[93],"show":[94],"combination":[96],"two":[98],"sensors":[99],"does":[100],"not":[101,138],"necessarily":[102],"result":[103],"an":[105],"improved":[106],"accuracy.":[107],"determined":[110],"best":[112],"results":[113,141],"are":[114],"obtained":[115,129],"by":[116],"extremely":[118],"randomized":[119],"trees":[120],"approach,":[121],"operating":[122],"precomputed":[124],"features":[125],"from":[130],"wrist":[132],"sensor.":[133],"Deep":[134],"architectures":[136],"did":[137],"produce":[139],"competitive":[140],"with":[142],"architecture.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}