{"id":"https://openalex.org/W4312539085","doi":"https://doi.org/10.1109/access.2022.3205112","title":"A Deep Learning Approach for Fatigue Prediction in Sports Using GPS Data and Rate of Perceived Exertion","display_name":"A Deep Learning Approach for Fatigue Prediction in Sports Using GPS Data and Rate of Perceived Exertion","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312539085","doi":"https://doi.org/10.1109/access.2022.3205112"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3205112","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3205112","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09881489.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/ielx7/6287639/9668973/09881489.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054291013","display_name":"Jeongbin Kim","orcid":"https://orcid.org/0000-0002-5950-0056"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jeongbin Kim","raw_affiliation_strings":["Fitogether Inc., Seoul, South Korea","Department of Industrial Engineering, Seoul National University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fitogether Inc., Seoul, South Korea","institution_ids":[]},{"raw_affiliation_string":"Department of Industrial Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100672200","display_name":"Hyunsung Kim","orcid":"https://orcid.org/0000-0002-6286-5160"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hyunsung Kim","raw_affiliation_strings":["Fitogether Inc., Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fitogether Inc., Seoul, South Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100626471","display_name":"Jonghyun Lee","orcid":"https://orcid.org/0000-0002-3646-2915"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jonghyun Lee","raw_affiliation_strings":["Fitogether Inc., Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fitogether Inc., Seoul, South Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052406194","display_name":"Jaechan Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jaechan Lee","raw_affiliation_strings":["Fitogether Inc., Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fitogether Inc., Seoul, South Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102719222","display_name":"Jinsung Yoon","orcid":"https://orcid.org/0000-0002-9420-9790"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinsung Yoon","raw_affiliation_strings":["Fitogether Inc., Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fitogether Inc., Seoul, South Korea","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011019318","display_name":"Sang\u2010Ki Ko","orcid":"https://orcid.org/0000-0002-5406-5104"},"institutions":[{"id":"https://openalex.org/I165507594","display_name":"Kangwon National University","ror":"https://ror.org/01mh5ph17","country_code":"KR","type":"education","lineage":["https://openalex.org/I165507594"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sang-Ki Ko","raw_affiliation_strings":["Fitogether Inc., Seoul, South Korea","Department of Computer Science & Engineering, Kangwon National University, Chuncheon, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-5406-5104","affiliations":[{"raw_affiliation_string":"Fitogether Inc., Seoul, South Korea","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Science & Engineering, Kangwon National University, Chuncheon, South Korea","institution_ids":["https://openalex.org/I165507594"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.5322,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.89737816,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"10","issue":null,"first_page":"103056","last_page":"103064"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10157","display_name":"Sports Performance and Training","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2732","display_name":"Orthopedics and Sports 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/T10157","display_name":"Sports Performance and Training","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2732","display_name":"Orthopedics and Sports Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11209","display_name":"Cardiovascular and exercise physiology","score":0.993399977684021,"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"}},{"id":"https://openalex.org/T12138","display_name":"Occupational Health and Performance","score":0.9715999960899353,"subfield":{"id":"https://openalex.org/subfields/3609","display_name":"Occupational Therapy"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.762529730796814},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6055851578712463},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.5919960141181946},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.568124532699585},{"id":"https://openalex.org/keywords/perceived-exertion","display_name":"Perceived exertion","score":0.5437374114990234},{"id":"https://openalex.org/keywords/rating-of-perceived-exertion","display_name":"Rating of perceived exertion","score":0.5046318769454956},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4515385925769806},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.4446144700050354},{"id":"https://openalex.org/keywords/jerk","display_name":"Jerk","score":0.4294235408306122},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4164988100528717},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3521006107330322},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.34270644187927246},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.28084784746170044},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20879125595092773},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14702585339546204},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.08504775166511536}],"concepts":[{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.762529730796814},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6055851578712463},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.5919960141181946},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.568124532699585},{"id":"https://openalex.org/C2993527604","wikidata":"https://www.wikidata.org/wiki/Q2372945","display_name":"Perceived exertion","level":4,"score":0.5437374114990234},{"id":"https://openalex.org/C2780928941","wikidata":"https://www.wikidata.org/wiki/Q2372945","display_name":"Rating of perceived exertion","level":4,"score":0.5046318769454956},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4515385925769806},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.4446144700050354},{"id":"https://openalex.org/C181605269","wikidata":"https://www.wikidata.org/wiki/Q497332","display_name":"Jerk","level":3,"score":0.4294235408306122},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4164988100528717},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3521006107330322},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.34270644187927246},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.28084784746170044},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20879125595092773},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14702585339546204},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.08504775166511536},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C2777953023","wikidata":"https://www.wikidata.org/wiki/Q1073121","display_name":"Heart rate","level":3,"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/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3205112","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3205112","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09881489.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:b2de60a6d89b41fc9bfafc365499da04","is_oa":true,"landing_page_url":"https://doaj.org/article/b2de60a6d89b41fc9bfafc365499da04","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 10, Pp 103056-103064 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3205112","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3205112","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09881489.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":[{"display_name":"Reduced inequalities","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320326061","display_name":"CHA University","ror":null},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4312539085.pdf","grobid_xml":"https://content.openalex.org/works/W4312539085.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W61751760","https://openalex.org/W1849277567","https://openalex.org/W1975425674","https://openalex.org/W2007509206","https://openalex.org/W2010139925","https://openalex.org/W2032725886","https://openalex.org/W2033435133","https://openalex.org/W2057332246","https://openalex.org/W2086600557","https://openalex.org/W2102375866","https://openalex.org/W2107685782","https://openalex.org/W2112379532","https://openalex.org/W2126040782","https://openalex.org/W2130058089","https://openalex.org/W2138834555","https://openalex.org/W2157227034","https://openalex.org/W2169915565","https://openalex.org/W2262849853","https://openalex.org/W2294109175","https://openalex.org/W2318847400","https://openalex.org/W2328912122","https://openalex.org/W2397341258","https://openalex.org/W2605954007","https://openalex.org/W2617129083","https://openalex.org/W2626840438","https://openalex.org/W2771098373","https://openalex.org/W2772264491","https://openalex.org/W2773200401","https://openalex.org/W2786172045","https://openalex.org/W2892035503","https://openalex.org/W2911968972","https://openalex.org/W2915939045","https://openalex.org/W2954971921","https://openalex.org/W2962858109","https://openalex.org/W2989923511","https://openalex.org/W3099125266","https://openalex.org/W6736249852"],"related_works":["https://openalex.org/W3137246329","https://openalex.org/W2325756313","https://openalex.org/W2796225271","https://openalex.org/W2471655736","https://openalex.org/W4391609050","https://openalex.org/W2612279534","https://openalex.org/W2565543676","https://openalex.org/W2985411952","https://openalex.org/W3114420751","https://openalex.org/W2369260392"],"abstract_inverted_index":{"Monitoring":[0],"players\u2019":[1,98,116],"fatigue":[2,18,63,220],"is":[3,36],"essential":[4],"to":[5,41,70,90,140,197,206],"maintaining":[6],"the":[7,23,26,54,72,120,136,158,180,186,189,199,207,214],"best":[8],"performance":[9],"of":[10,17,29,50,93,102,146,188,216,228],"players":[11],"during":[12,127],"sports":[13],"games.":[14],"The":[15],"level":[16],"can":[19],"be":[20],"measured":[21],"by":[22,112],"external":[24,57,73],"workload,":[25,34,74],"aggregated":[27,68,103],"amount":[28],"physical":[30],"activity":[31],"or":[32],"internal":[33,59],"which":[35],"an":[37],"individual\u2019s":[38],"psycho-physiological":[39],"response":[40],"that":[42,203],"activity.":[43],"There":[44],"have":[45],"been":[46],"a":[47,86,128],"growing":[48],"number":[49],"studies":[51],"focusing":[52],"on":[53,224],"relationship":[55],"between":[56],"and":[58,107,119,124,143,149,169,218],"workloads":[60],"for":[61],"efficient":[62],"monitoring.":[64],"However,":[65],"they":[66],"utilize":[67],"features":[69],"represent":[71],"losing":[75],"raw":[76,137],"data":[77,100,118,139,231],"details":[78],"such":[79],"as":[80],"sequential":[81],"information.":[82],"This":[83],"study":[84],"proposes":[85],"deep":[87,225],"learning":[88,226],"algorithm":[89],"predict":[91],"Rate":[92],"Perceived":[94],"Exertion":[95],"(RPE)":[96],"from":[97,122,233],"movement":[99,117,182],"instead":[101,227],"features.":[104,183],"Electronic":[105],"Performance":[106],"Tracking":[108],"Systems":[109],"(EPTS)":[110],"powered":[111],"GPS":[113,138],"sensors":[114],"collected":[115],"RPE":[121,159],"training":[123],"match":[125],"sessions":[126],"Korean":[129],"professional":[130],"soccer":[131],"team":[132],"season.":[133],"We":[134],"preprocessed":[135,181],"obtain":[141],"linear":[142],"angular":[144],"components":[145],"velocity,":[147],"acceleration,":[148],"jerk.":[150],"Our":[151,210],"proposed":[152],"model,":[153],"named":[154],"FatigueNet,":[155,190],"effectively":[156],"predicted":[157],"with":[160],"mean":[161,171],"absolute":[162],"error":[163,173],"(MAE)":[164],"=":[165,175],"0.8494":[166],"\u00b1":[167,177],"0.0557":[168],"root":[170],"square":[172],"(RMSE)":[174],"1.2166":[176],"0.0737":[178],"using":[179],"To":[184],"interpret":[185],"predictions":[187],"we":[191],"also":[192],"performed":[193],"regression":[194],"activation":[195],"mapping":[196],"localize":[198],"discriminative":[200],"time":[201],"intervals":[202],"contributed":[204],"more":[205],"prediction":[208],"results.":[209],"experimental":[211],"results":[212],"imply":[213],"possibility":[215],"automated":[217],"objective":[219],"monitoring":[221],"systems":[222],"based":[223],"arduous":[229],"manual":[230],"collection":[232],"players.":[234]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}