{"id":"https://openalex.org/W2028990718","doi":"https://doi.org/10.1109/cidm.2014.7008685","title":"Recognizing gym exercises using acceleration data from wearable sensors","display_name":"Recognizing gym exercises using acceleration data from wearable sensors","publication_year":2014,"publication_date":"2014-12-01","ids":{"openalex":"https://openalex.org/W2028990718","doi":"https://doi.org/10.1109/cidm.2014.7008685","mag":"2028990718"},"language":"en","primary_location":{"id":"doi:10.1109/cidm.2014.7008685","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cidm.2014.7008685","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5053650091","display_name":"Heli Koskim\u00e4ki","orcid":"https://orcid.org/0000-0003-2760-2071"},"institutions":[{"id":"https://openalex.org/I98381234","display_name":"University of Oulu","ror":"https://ror.org/03yj89h83","country_code":"FI","type":"education","lineage":["https://openalex.org/I98381234"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Heli Koskimaki","raw_affiliation_strings":["Computer Science and Engineering Department, University of Oulu, Oulu, FI, Finland","Computer Science and Engineering Department, P.O. BOX 4500, FI-90014, University of Oulu, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, University of Oulu, Oulu, FI, Finland","institution_ids":["https://openalex.org/I98381234"]},{"raw_affiliation_string":"Computer Science and Engineering Department, P.O. BOX 4500, FI-90014, University of Oulu, Finland","institution_ids":["https://openalex.org/I98381234"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069221764","display_name":"Pekka Siirtola","orcid":"https://orcid.org/0000-0002-5995-5421"},"institutions":[{"id":"https://openalex.org/I98381234","display_name":"University of Oulu","ror":"https://ror.org/03yj89h83","country_code":"FI","type":"education","lineage":["https://openalex.org/I98381234"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Pekka Siirtola","raw_affiliation_strings":["Computer Science and Engineering Department, University of Oulu, Oulu, FI, Finland","Computer Science and Engineering Department, P.O. BOX 4500, FI-90014, University of Oulu, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, University of Oulu, Oulu, FI, Finland","institution_ids":["https://openalex.org/I98381234"]},{"raw_affiliation_string":"Computer Science and Engineering Department, P.O. BOX 4500, FI-90014, University of Oulu, Finland","institution_ids":["https://openalex.org/I98381234"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I98381234"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"321","last_page":"328"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9991999864578247,"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":0.9991999864578247,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9948999881744385,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.7079353928565979},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.7075538635253906},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6929028034210205},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5489025712013245},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5074993968009949},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4710134267807007},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.4618481695652008},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4293975830078125},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4250189960002899},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39752906560897827},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38481032848358154},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17923882603645325},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09334170818328857},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.09104430675506592}],"concepts":[{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.7079353928565979},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.7075538635253906},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6929028034210205},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5489025712013245},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5074993968009949},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4710134267807007},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.4618481695652008},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4293975830078125},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4250189960002899},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39752906560897827},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38481032848358154},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17923882603645325},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09334170818328857},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.09104430675506592},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cidm.2014.7008685","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cidm.2014.7008685","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321108","display_name":"Academy of Finland","ror":"https://ror.org/05k73zm37"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1414062319","https://openalex.org/W1967320885","https://openalex.org/W1975186942","https://openalex.org/W2060233269","https://openalex.org/W2067299273","https://openalex.org/W2085090498","https://openalex.org/W2096680959","https://openalex.org/W2110729448","https://openalex.org/W2121381553","https://openalex.org/W2127127580","https://openalex.org/W2140561855","https://openalex.org/W2156329326","https://openalex.org/W2160594359","https://openalex.org/W2404903144","https://openalex.org/W2556902169","https://openalex.org/W2613161123","https://openalex.org/W2747485148","https://openalex.org/W4239167631","https://openalex.org/W4256561644","https://openalex.org/W6642162515","https://openalex.org/W6671756550","https://openalex.org/W6713072065"],"related_works":["https://openalex.org/W3195649134","https://openalex.org/W2281498195","https://openalex.org/W2390829436","https://openalex.org/W1971289376","https://openalex.org/W1989791859","https://openalex.org/W2506504620","https://openalex.org/W2565094479","https://openalex.org/W3105278570","https://openalex.org/W2117913171","https://openalex.org/W2582769230"],"abstract_inverted_index":{"The":[0,94,136],"activity":[1,51,78,107],"recognition":[2,52,96,108],"approaches":[3],"can":[4,161,170],"be":[5,162,171],"used":[6,70,124],"for":[7,188,202],"entertainment,":[8],"to":[9,18,75,82,125],"give":[10],"people":[11,22],"information":[12],"about":[13],"their":[14,24],"own":[15],"behavior,":[16],"and":[17,20,47,115,164],"monitor":[19],"supervise":[21],"through":[23],"actions.":[25],"Thus,":[26],"it":[27],"is":[28,69,97,113,123],"a":[29,179],"natural":[30],"consequence":[31],"of":[32,38,50,88,109],"that":[33,35,139],"fact":[34],"the":[36,57,73,104,117,120,146,167,174,184,197],"amount":[37],"wearable":[39],"sensors":[40],"based":[41],"studies":[42],"has":[43],"increased":[44],"as":[45],"well,":[46],"new":[48],"applications":[49],"are":[53],"being":[54],"invented":[55],"in":[56,72,116,131,193],"process.":[58],"In":[59,103],"this":[60,194],"study,":[61],"gym":[62,132],"data,":[63],"including":[64],"36":[65],"different":[66,101,142,198,204],"exercise":[67,90,143,150,168],"classes,":[68,190],"aiming":[71],"future":[74],"create":[76],"automatic":[77],"diaries":[79],"showing":[80],"reliably":[81],"end":[83],"users":[84],"how":[85],"many":[86],"sets":[87,144,199],"given":[89],"have":[91],"been":[92],"performed.":[93,135],"actual":[95,128],"divided":[98],"into":[99],"two":[100],"steps.":[102],"first":[105],"step,":[106],"certain":[110],"time":[111],"intervals":[112],"performed":[114],"second":[118],"step":[119],"state-machine":[121,175],"approach":[122],"decide":[126],"when":[127,140],"events":[129,169],"(sets":[130],"data)":[133],"were":[134,200],"results":[137],"showed":[138],"recognizing":[141],"from":[145],"same":[147],"occasion":[148],"(sequential":[149],"sets),":[151],"on":[152],"average,":[153],"over":[154],"96":[155],"percent":[156],"window-wise":[157],"true":[158],"positive":[159],"rate":[160],"achieved,":[163],"moreover,":[165],"all":[166,196],"discovered":[172,201],"using":[173,178],"approach.":[176],"When":[177],"separate":[180],"validation":[181],"test":[182],"set,":[183],"accuracies":[185],"decreased":[186],"significantly":[187],"some":[189],"but":[191],"even":[192],"case,":[195],"26":[203],"classes.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}