{"id":"https://openalex.org/W2538636357","doi":"https://doi.org/10.1109/embc.2016.7591786","title":"Applying neural network to VO<inf>2</inf> estimation using 6-axis motion sensing data","display_name":"Applying neural network to VO<inf>2</inf> estimation using 6-axis motion sensing data","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2538636357","doi":"https://doi.org/10.1109/embc.2016.7591786","mag":"2538636357","pmid":"https://pubmed.ncbi.nlm.nih.gov/28269330"},"language":"en","primary_location":{"id":"doi:10.1109/embc.2016.7591786","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2016.7591786","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","pubmed"],"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/A5038626211","display_name":"Naoteru Nakamura","orcid":null},"institutions":[{"id":"https://openalex.org/I56624758","display_name":"Kansai University","ror":"https://ror.org/03xg1f311","country_code":"JP","type":"education","lineage":["https://openalex.org/I56624758"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naoteru Nakamura","raw_affiliation_strings":["Graduate School of Engineering Science, Kansai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering Science, Kansai University","institution_ids":["https://openalex.org/I56624758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103643113","display_name":"Takashi Nagata","orcid":null},"institutions":[{"id":"https://openalex.org/I56624758","display_name":"Kansai University","ror":"https://ror.org/03xg1f311","country_code":"JP","type":"education","lineage":["https://openalex.org/I56624758"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takashi Nagata","raw_affiliation_strings":["Graduate School of Engineering Science, Kansai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering Science, Kansai University","institution_ids":["https://openalex.org/I56624758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022619890","display_name":"Masato Miyatake","orcid":null},"institutions":[{"id":"https://openalex.org/I56624758","display_name":"Kansai University","ror":"https://ror.org/03xg1f311","country_code":"JP","type":"education","lineage":["https://openalex.org/I56624758"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masato Miyatake","raw_affiliation_strings":["Graduate School of Engineering Science, Kansai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering Science, Kansai University","institution_ids":["https://openalex.org/I56624758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075932526","display_name":"Akira Yuuki","orcid":null},"institutions":[{"id":"https://openalex.org/I56624758","display_name":"Kansai University","ror":"https://ror.org/03xg1f311","country_code":"JP","type":"education","lineage":["https://openalex.org/I56624758"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akira Yuuki","raw_affiliation_strings":["Graduate School of Engineering Science, Kansai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering Science, Kansai University","institution_ids":["https://openalex.org/I56624758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058992038","display_name":"Hiroyuki Yomo","orcid":"https://orcid.org/0000-0001-9177-317X"},"institutions":[{"id":"https://openalex.org/I56624758","display_name":"Kansai University","ror":"https://ror.org/03xg1f311","country_code":"JP","type":"education","lineage":["https://openalex.org/I56624758"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroyuki Yomo","raw_affiliation_strings":["Graduate School of Engineering Science, Kansai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering Science, Kansai University","institution_ids":["https://openalex.org/I56624758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112420472","display_name":"Takashi Kawabata","orcid":null},"institutions":[{"id":"https://openalex.org/I56624758","display_name":"Kansai University","ror":"https://ror.org/03xg1f311","country_code":"JP","type":"education","lineage":["https://openalex.org/I56624758"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takashi Kawabata","raw_affiliation_strings":["Graduate School of Health and Well-being, Kansai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Health and Well-being, Kansai University","institution_ids":["https://openalex.org/I56624758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061363370","display_name":"Shinsuke Hara","orcid":"https://orcid.org/0000-0002-5183-9725"},"institutions":[{"id":"https://openalex.org/I317356780","display_name":"Osaka City University","ror":"https://ror.org/02skfsw40","country_code":"JP","type":"education","lineage":["https://openalex.org/I317356780"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shinsuke Hara","raw_affiliation_strings":["Graduate School of Engineering, Osaka City University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Osaka City University","institution_ids":["https://openalex.org/I317356780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"58","issue":null,"first_page":"4739","last_page":"4742"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9782000184059143,"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"}},"topics":[{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9782000184059143,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9715999960899353,"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":0.9531999826431274,"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/angular-velocity","display_name":"Angular velocity","score":0.7232565879821777},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.7218454480171204},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7142926454544067},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.5975991487503052},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5750504732131958},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5713214874267578},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5309808850288391},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5126480460166931},{"id":"https://openalex.org/keywords/angular-acceleration","display_name":"Angular acceleration","score":0.49035096168518066},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4537719190120697},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.41378918290138245},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.27038824558258057},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25978073477745056},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.20448490977287292},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.192836195230484},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15339738130569458}],"concepts":[{"id":"https://openalex.org/C5594486","wikidata":"https://www.wikidata.org/wiki/Q161635","display_name":"Angular velocity","level":2,"score":0.7232565879821777},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.7218454480171204},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7142926454544067},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5975991487503052},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5750504732131958},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5713214874267578},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5309808850288391},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5126480460166931},{"id":"https://openalex.org/C190704821","wikidata":"https://www.wikidata.org/wiki/Q186300","display_name":"Angular acceleration","level":3,"score":0.49035096168518066},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4537719190120697},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.41378918290138245},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27038824558258057},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25978073477745056},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.20448490977287292},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.192836195230484},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15339738130569458},{"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/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000054","descriptor_name":"Acceleration","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000054","descriptor_name":"Acceleration","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000054","descriptor_name":"Acceleration","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009038","descriptor_name":"Motion","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009038","descriptor_name":"Motion","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009038","descriptor_name":"Motion","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009716","descriptor_name":"Numerical Analysis, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009716","descriptor_name":"Numerical Analysis, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009716","descriptor_name":"Numerical Analysis, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D010101","descriptor_name":"Oxygen Consumption","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D010101","descriptor_name":"Oxygen Consumption","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D010101","descriptor_name":"Oxygen Consumption","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D015444","descriptor_name":"Exercise","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015444","descriptor_name":"Exercise","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015444","descriptor_name":"Exercise","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016014","descriptor_name":"Linear Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016014","descriptor_name":"Linear Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016014","descriptor_name":"Linear Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D055815","descriptor_name":"Young Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055815","descriptor_name":"Young Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055815","descriptor_name":"Young Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc.2016.7591786","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2016.7591786","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:28269330","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28269330","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":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1663973292","https://openalex.org/W1983736874","https://openalex.org/W1999678136","https://openalex.org/W2016915880","https://openalex.org/W2069889533","https://openalex.org/W2091875500","https://openalex.org/W2138572279","https://openalex.org/W2138934389","https://openalex.org/W2149059821","https://openalex.org/W2164041372","https://openalex.org/W2171887141","https://openalex.org/W2323421459","https://openalex.org/W2330493593","https://openalex.org/W2470599152","https://openalex.org/W3047078416","https://openalex.org/W4212863985","https://openalex.org/W6685203846"],"related_works":["https://openalex.org/W2370252541","https://openalex.org/W2628866709","https://openalex.org/W123316752","https://openalex.org/W845993790","https://openalex.org/W2329650644","https://openalex.org/W1973219514","https://openalex.org/W2275557598","https://openalex.org/W2067537352","https://openalex.org/W1510705688","https://openalex.org/W2084330080"],"abstract_inverted_index":{"This":[0],"paper":[1],"focuses":[2],"on":[3,95,108,151],"oxygen":[4],"consumption":[5],"(VO2)":[6],"estimation":[7,38,117,137],"using":[8],"6-axis":[9],"motion":[10,23,64],"data":[11,57,66,121],"(3-axis":[12],"acceleration":[13,120],"and":[14,63,146],"3-axis":[15],"angular":[16,109,153],"velocity)":[17],"that":[18,52,127],"are":[19],"obtained":[20],"from":[21],"small":[22],"sensors":[24],"attached":[25],"to":[26,35,141,159],"people":[27,68],"playing":[28],"sports":[29],"with":[30,69,91,115,118],"different":[31],"intensities.":[32],"In":[33],"order":[34],"achieve":[36],"high":[37],"accuracy":[39,90,138,162],"over":[40,163],"a":[41,70],"wide":[42,71],"range":[43,72],"of":[44,46,59,67,73,75,149,166],"intensities":[45,74,165],"exercises,":[47],"we":[48,101],"apply":[49],"neural":[50,85,132],"network":[51,86,133],"is":[53],"trained":[54],"by":[55,83,87],"experimental":[56],"consisting":[58],"the":[60,80,96,106,116,119,128,136,142,147,152,161],"measured":[61],"VO2":[62],"sensing":[65],"exercises.":[76,167],"We":[77],"first":[78],"investigate":[79],"gain":[81],"brought":[82],"applying":[84],"comparing":[88],"its":[89],"an":[92,156],"approach":[93],"based":[94],"linear":[97,143],"regression":[98,144],"model.":[99],"Then,":[100],"analyze":[102],"how":[103],"much":[104],"improvement":[105],"information":[107,150],"velocity":[110,154],"can":[111,134],"bring":[112],"as":[113],"compared":[114],"alone.":[122],"Our":[123],"numerical":[124],"results":[125],"show":[126],"employed":[129],"framework":[130],"exploiting":[131],"improve":[135,160],"in":[139],"comparison":[140],"model":[145],"exploitation":[148],"plays":[155],"important":[157],"role":[158],"higher":[164]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2016-10-28T00:00:00"}