{"id":"https://openalex.org/W2905471781","doi":"https://doi.org/10.1109/gcce.2018.8574483","title":"Physical Burden Prediction for Cycling on Arbitrary Route","display_name":"Physical Burden Prediction for Cycling on Arbitrary Route","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2905471781","doi":"https://doi.org/10.1109/gcce.2018.8574483","mag":"2905471781"},"language":"en","primary_location":{"id":"doi:10.1109/gcce.2018.8574483","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce.2018.8574483","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 7th Global Conference on Consumer Electronics (GCCE)","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/A5032122149","display_name":"Wang Chine wei","orcid":null},"institutions":[{"id":"https://openalex.org/I92582371","display_name":"Southern Taiwan University of Science and Technology","ror":"https://ror.org/0029n1t76","country_code":"TW","type":"education","lineage":["https://openalex.org/I92582371"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wang Chine wei","raw_affiliation_strings":["Southern Taiwan University of Science and Technology, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern Taiwan University of Science and Technology, Taiwan","institution_ids":["https://openalex.org/I92582371"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073484126","display_name":"Teruhiro Mizumoto","orcid":"https://orcid.org/0000-0003-0281-1205"},"institutions":[{"id":"https://openalex.org/I75917431","display_name":"Nara Institute of Science and Technology","ror":"https://ror.org/05bhada84","country_code":"JP","type":"education","lineage":["https://openalex.org/I75917431"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Teruhiro Mizumoto","raw_affiliation_strings":["Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan","institution_ids":["https://openalex.org/I75917431"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019740585","display_name":"Keiichi Yasumoto","orcid":"https://orcid.org/0000-0003-1579-3237"},"institutions":[{"id":"https://openalex.org/I75917431","display_name":"Nara Institute of Science and Technology","ror":"https://ror.org/05bhada84","country_code":"JP","type":"education","lineage":["https://openalex.org/I75917431"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keiichi Yasumoto","raw_affiliation_strings":["Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan","institution_ids":["https://openalex.org/I75917431"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"192","last_page":"193"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11209","display_name":"Cardiovascular and exercise physiology","score":0.9491999745368958,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11209","display_name":"Cardiovascular and exercise physiology","score":0.9491999745368958,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cycling","display_name":"Cycling","score":0.8573534488677979},{"id":"https://openalex.org/keywords/cadence","display_name":"Cadence","score":0.8146816492080688},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6487876176834106},{"id":"https://openalex.org/keywords/heart-rate","display_name":"Heart rate","score":0.5130337476730347},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.506672203540802},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.35643550753593445},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27384912967681885},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15386426448822021},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.08576846122741699}],"concepts":[{"id":"https://openalex.org/C541528975","wikidata":"https://www.wikidata.org/wiki/Q53121","display_name":"Cycling","level":2,"score":0.8573534488677979},{"id":"https://openalex.org/C2777125575","wikidata":"https://www.wikidata.org/wiki/Q14088448","display_name":"Cadence","level":2,"score":0.8146816492080688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6487876176834106},{"id":"https://openalex.org/C2777953023","wikidata":"https://www.wikidata.org/wiki/Q1073121","display_name":"Heart rate","level":3,"score":0.5130337476730347},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.506672203540802},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.35643550753593445},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27384912967681885},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15386426448822021},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.08576846122741699},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"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/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce.2018.8574483","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce.2018.8574483","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 7th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":1,"referenced_works":["https://openalex.org/W2004844047"],"related_works":["https://openalex.org/W2022589540","https://openalex.org/W1504227784","https://openalex.org/W2273474689","https://openalex.org/W2060087341","https://openalex.org/W2162827184","https://openalex.org/W1970486345","https://openalex.org/W2087602370","https://openalex.org/W1977039811","https://openalex.org/W2317989293","https://openalex.org/W2077601906"],"abstract_inverted_index":{"In":[0,30],"this":[1],"study,":[2],"we":[3,34,49,81],"propose":[4],"a":[5,15],"method":[6,64],"for":[7,11,56],"informing":[8],"physical":[9,25,37,67],"load":[10,68],"each":[12,57],"section":[13],"of":[14,39,95,109,112],"specified":[16],"cycling":[17,93,100],"route":[18,94],"to":[19],"the":[20,36,51,66,71,76,83,110,113,119,123,128],"cyclist":[21],"depending":[22],"on":[23,70],"own":[24],"ability":[26],"before":[27],"starting":[28],"cycling.":[29],"our":[31,63],"method,":[32],"firstly,":[33],"cluster":[35],"abilities":[38],"cyclists":[40],"into":[41],"categories":[42],"by":[43,59,88],"Gaussian":[44],"mixture":[45],"model":[46,55,117],"(GMM).":[47],"Secondly,":[48],"build":[50,75],"heart":[52,72,77,114,130,134],"rate":[53,78,115,131,135],"prediction":[54,79,116,125],"category":[58],"machine":[60],"learning.":[61],"Finally,":[62],"predicts":[65],"based":[69],"rate.":[73],"To":[74],"model,":[80],"use":[82],"open":[84],"accesses":[85],"data":[86,120],"provided":[87],"Strava.":[89],"These":[90],"datasets":[91],"include":[92],"altitude,":[96],"distance,":[97],"gradient":[98],"and":[99,132],"cadence,":[101],"speed,":[102],"oxygen":[103],"uptake,":[104],"power,":[105],"time.":[106],"The":[107],"result":[108],"evaluation":[111],"using":[118],"sets":[121],"shows":[122],"average":[124],"error":[126],"between":[127],"measured":[129],"predicted":[133],"is":[136],"1.4833.":[137]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}