{"id":"https://openalex.org/W2994834685","doi":"https://doi.org/10.1109/access.2019.2959398","title":"Physical Workout Classification Using Wrist Accelerometer Data by Deep Convolutional Neural Networks","display_name":"Physical Workout Classification Using Wrist Accelerometer Data by Deep Convolutional Neural Networks","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2994834685","doi":"https://doi.org/10.1109/access.2019.2959398","mag":"2994834685"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2959398","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2959398","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08932483.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/ielx7/6287639/8600701/08932483.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078058688","display_name":"Pilyeong Jeong","orcid":"https://orcid.org/0000-0002-5314-9605"},"institutions":[{"id":"https://openalex.org/I146429904","display_name":"Incheon National University","ror":"https://ror.org/02xf7p935","country_code":"KR","type":"education","lineage":["https://openalex.org/I146429904"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Pilyeong Jeong","raw_affiliation_strings":["Department of Electronics Engineering, Incheon National University (INU), Incheon, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-5314-9605","affiliations":[{"raw_affiliation_string":"Department of Electronics Engineering, Incheon National University (INU), Incheon, South Korea","institution_ids":["https://openalex.org/I146429904"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076554280","display_name":"Mungyeong Choe","orcid":"https://orcid.org/0000-0003-4964-1987"},"institutions":[{"id":"https://openalex.org/I146429904","display_name":"Incheon National University","ror":"https://ror.org/02xf7p935","country_code":"KR","type":"education","lineage":["https://openalex.org/I146429904"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Mungyeong Choe","raw_affiliation_strings":["Department of Industrial and Management Engineering, Incheon National University (INU), Incheon, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-4964-1987","affiliations":[{"raw_affiliation_string":"Department of Industrial and Management Engineering, Incheon National University (INU), Incheon, South Korea","institution_ids":["https://openalex.org/I146429904"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043260833","display_name":"Nahyeong Kim","orcid":"https://orcid.org/0000-0001-5438-3359"},"institutions":[{"id":"https://openalex.org/I146429904","display_name":"Incheon National University","ror":"https://ror.org/02xf7p935","country_code":"KR","type":"education","lineage":["https://openalex.org/I146429904"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Nahyeong Kim","raw_affiliation_strings":["Department of Industrial and Management Engineering, Incheon National University (INU), Incheon, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-5438-3359","affiliations":[{"raw_affiliation_string":"Department of Industrial and Management Engineering, Incheon National University (INU), Incheon, South Korea","institution_ids":["https://openalex.org/I146429904"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100618956","display_name":"Jaehyun Park","orcid":"https://orcid.org/0000-0002-5264-6941"},"institutions":[{"id":"https://openalex.org/I146429904","display_name":"Incheon National University","ror":"https://ror.org/02xf7p935","country_code":"KR","type":"education","lineage":["https://openalex.org/I146429904"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaehyun Park","raw_affiliation_strings":["Department of Industrial and Management Engineering, Incheon National University (INU), Incheon, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-5264-6941","affiliations":[{"raw_affiliation_string":"Department of Industrial and Management Engineering, Incheon National University (INU), Incheon, South Korea","institution_ids":["https://openalex.org/I146429904"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006563419","display_name":"Jaeyong Chung","orcid":"https://orcid.org/0000-0001-5819-1995"},"institutions":[{"id":"https://openalex.org/I146429904","display_name":"Incheon National University","ror":"https://ror.org/02xf7p935","country_code":"KR","type":"education","lineage":["https://openalex.org/I146429904"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaeyong Chung","raw_affiliation_strings":["Department of Electronics Engineering, Incheon National University (INU), Incheon, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-5819-1995","affiliations":[{"raw_affiliation_string":"Department of Electronics Engineering, Incheon National University (INU), Incheon, South Korea","institution_ids":["https://openalex.org/I146429904"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5078058688"],"corresponding_institution_ids":["https://openalex.org/I146429904"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.14847082,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"7","issue":null,"first_page":"182406","last_page":"182414"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9907000064849854,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9801999926567078,"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":0.7474408149719238},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7177718877792358},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7113184928894043},{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.6429344415664673},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6081941723823547},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5849967002868652},{"id":"https://openalex.org/keywords/squat","display_name":"Squat","score":0.5807105898857117},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5209259390830994},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4756621718406677},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4693794250488281},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4620617628097534},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.4474131464958191},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41686180233955383},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3889831304550171},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.1204937994480133}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7474408149719238},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7177718877792358},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7113184928894043},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.6429344415664673},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6081941723823547},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5849967002868652},{"id":"https://openalex.org/C2778820510","wikidata":"https://www.wikidata.org/wiki/Q1755746","display_name":"Squat","level":2,"score":0.5807105898857117},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5209259390830994},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4756621718406677},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4693794250488281},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4620617628097534},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.4474131464958191},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41686180233955383},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3889831304550171},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.1204937994480133},{"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/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"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/access.2019.2959398","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2959398","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08932483.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:96e8472a2e894c7abb25112c18bb1d9d","is_oa":true,"landing_page_url":"https://doaj.org/article/96e8472a2e894c7abb25112c18bb1d9d","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 7, Pp 182406-182414 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2959398","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2959398","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08932483.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":[],"awards":[{"id":"https://openalex.org/G4112560349","display_name":null,"funder_award_id":"2018R1C1B6008848","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322030","display_name":"Ministry of Science, ICT and Future Planning","ror":"https://ror.org/032e49973"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2994834685.pdf","grobid_xml":"https://content.openalex.org/works/W2994834685.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W602397586","https://openalex.org/W1762028752","https://openalex.org/W1975428667","https://openalex.org/W1991539813","https://openalex.org/W2002261403","https://openalex.org/W2051552261","https://openalex.org/W2054780155","https://openalex.org/W2064675550","https://openalex.org/W2114705933","https://openalex.org/W2117794119","https://openalex.org/W2121969814","https://openalex.org/W2140013239","https://openalex.org/W2163605009","https://openalex.org/W2168538666","https://openalex.org/W2170931123","https://openalex.org/W2270470215","https://openalex.org/W2465142829","https://openalex.org/W2509293058","https://openalex.org/W2547204915","https://openalex.org/W2582781338","https://openalex.org/W2791139105","https://openalex.org/W2963855167","https://openalex.org/W3204438512","https://openalex.org/W6678509853","https://openalex.org/W6680761501","https://openalex.org/W6684191040","https://openalex.org/W6704286305","https://openalex.org/W6948151307"],"related_works":["https://openalex.org/W2035481409","https://openalex.org/W2765080098","https://openalex.org/W2385749422","https://openalex.org/W2355290145","https://openalex.org/W2353465659","https://openalex.org/W2009888974","https://openalex.org/W4384517610","https://openalex.org/W4288389100","https://openalex.org/W1902800522","https://openalex.org/W2339469482"],"abstract_inverted_index":{"Recently,":[0],"the":[1,32,46,87,123,131],"deep":[2,29,103],"learning":[3,30],"algorithm":[4],"has":[5],"received":[6],"considerable":[7],"attention":[8],"and":[9,60,101],"is":[10,23],"influencing":[11],"different":[12,90,134],"fields":[13],"including":[14,92],"human-computer":[15],"interaction":[16],"(HCI).":[17],"The":[18,107,113],"purpose":[19],"of":[20,34,115,125,133],"this":[21,116],"study":[22],"to":[24,31,41,66,122,130],"maximize":[25],"accuracy":[26,108],"by":[27],"applying":[28],"classification":[33,124,132],"body":[35],"movements.":[36],"An":[37],"experiment":[38,117],"was":[39,86,109],"performed":[40],"collect":[42],"acceleration":[43],"information":[44],"on":[45],"wrist":[47],"while":[48],"performing":[49],"seven":[50],"workouts:":[51],"pull":[52],"up,":[53],"row-barbell,":[54],"bench":[55],"press,":[56],"dips,":[57],"squat,":[58],"deadlift,":[59],"military":[61],"press.":[62],"Participants":[63],"were":[64],"asked":[65],"perform":[67],"each":[68],"workout":[69],"for":[70],"ten":[71,74],"sets":[72],"repeated":[73],"times":[75],"per":[76],"set.":[77],"Experimental":[78],"results":[79,114],"confirm":[80],"that":[81],"one-dimensional":[82],"convolutional":[83,104],"neural":[84,105],"network":[85],"best":[88],"among":[89],"algorithms":[91],"support":[93],"vector":[94],"machine,":[95],"multi-layer":[96],"perceptron,":[97],"long":[98],"short-term":[99],"memory,":[100],"other":[102],"networks.":[106],"extremely":[110],"high,":[111],"96%.":[112],"are":[118],"applicable":[119],"not":[120],"only":[121],"fitness":[126],"activities":[127],"but":[128],"also":[129],"motions":[135],"in":[136],"numerous":[137],"sporting":[138],"events.":[139]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}