{"id":"https://openalex.org/W3163971122","doi":"https://doi.org/10.1155/2021/9993677","title":"Sports Injury Rehabilitation Intervention Algorithm Based on Visual Analysis Technology","display_name":"Sports Injury Rehabilitation Intervention Algorithm Based on Visual Analysis Technology","publication_year":2021,"publication_date":"2021-05-22","ids":{"openalex":"https://openalex.org/W3163971122","doi":"https://doi.org/10.1155/2021/9993677","mag":"3163971122"},"language":"en","primary_location":{"id":"doi:10.1155/2021/9993677","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/9993677","pdf_url":"https://downloads.hindawi.com/journals/misy/2021/9993677.pdf","source":{"id":"https://openalex.org/S152111507","display_name":"Mobile Information Systems","issn_l":"1574-017X","issn":["1574-017X","1875-905X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mobile Information Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/misy/2021/9993677.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100673057","display_name":"Xiao Chen","orcid":"https://orcid.org/0000-0003-4632-0811"},"institutions":[{"id":"https://openalex.org/I158934434","display_name":"Zhongnan University of Economics and Law","ror":"https://ror.org/04yqxxq63","country_code":"CN","type":"education","lineage":["https://openalex.org/I158934434"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Chen","raw_affiliation_strings":["Physical Education Department, Zhongnan University of Economics and Law, Wuhan 430073, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Physical Education Department, Zhongnan University of Economics and Law, Wuhan 430073, Hubei, China","institution_ids":["https://openalex.org/I158934434"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049811545","display_name":"Guoliang Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I164946172","display_name":"Hengshui University","ror":"https://ror.org/03xvjtz09","country_code":"CN","type":"education","lineage":["https://openalex.org/I164946172"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guoliang Yuan","raw_affiliation_strings":["College of Physical Education, Hengshui University, Hengshui 053000, Hebei, China"],"raw_orcid":"https://orcid.org/0000-0003-2602-5030","affiliations":[{"raw_affiliation_string":"College of Physical Education, Hengshui University, Hengshui 053000, Hebei, China","institution_ids":["https://openalex.org/I164946172"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5049811545"],"corresponding_institution_ids":["https://openalex.org/I164946172"],"apc_list":{"value":2100,"currency":"USD","value_usd":2100},"apc_paid":{"value":2100,"currency":"USD","value_usd":2100},"fwci":3.1283,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.92549638,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"2021","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13647","display_name":"AI and Big Data Applications","score":0.982699990272522,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13647","display_name":"AI and Big Data Applications","score":0.982699990272522,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T14413","display_name":"Advanced Technologies in Various Fields","score":0.9696000218391418,"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/T13567","display_name":"AI and Multimedia in Education","score":0.9420999884605408,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8557798862457275},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6816313862800598},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6552035212516785},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5547767281532288},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5187392830848694},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5064476728439331},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47567668557167053},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43724918365478516},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.41238340735435486},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37210625410079956},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2806876301765442}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8557798862457275},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6816313862800598},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6552035212516785},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5547767281532288},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5187392830848694},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5064476728439331},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47567668557167053},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43724918365478516},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.41238340735435486},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37210625410079956},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2806876301765442},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1155/2021/9993677","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/9993677","pdf_url":"https://downloads.hindawi.com/journals/misy/2021/9993677.pdf","source":{"id":"https://openalex.org/S152111507","display_name":"Mobile Information Systems","issn_l":"1574-017X","issn":["1574-017X","1875-905X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mobile Information Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9c8b408888af481a90444740338fbaef","is_oa":true,"landing_page_url":"https://doaj.org/article/9c8b408888af481a90444740338fbaef","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":"Mobile Information Systems, Vol 2021 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2021/9993677","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/9993677","pdf_url":"https://downloads.hindawi.com/journals/misy/2021/9993677.pdf","source":{"id":"https://openalex.org/S152111507","display_name":"Mobile Information Systems","issn_l":"1574-017X","issn":["1574-017X","1875-905X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mobile Information Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3163971122.pdf","grobid_xml":"https://content.openalex.org/works/W3163971122.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W325178781","https://openalex.org/W2061043650","https://openalex.org/W2104956067","https://openalex.org/W2132691216","https://openalex.org/W2547176344","https://openalex.org/W2567521427","https://openalex.org/W2581449697","https://openalex.org/W2587337570","https://openalex.org/W2587415260","https://openalex.org/W2917863084","https://openalex.org/W2950103874","https://openalex.org/W2950125574","https://openalex.org/W2982409399","https://openalex.org/W3011955763","https://openalex.org/W3014586865","https://openalex.org/W3084580190","https://openalex.org/W3085519426","https://openalex.org/W3090239664","https://openalex.org/W3110708050","https://openalex.org/W3111255625","https://openalex.org/W3115462576","https://openalex.org/W3119855172","https://openalex.org/W3138953622","https://openalex.org/W3154205755","https://openalex.org/W6786875736"],"related_works":["https://openalex.org/W2560215812","https://openalex.org/W2149537132","https://openalex.org/W2964954556","https://openalex.org/W3019910406","https://openalex.org/W4386858688","https://openalex.org/W3034421924","https://openalex.org/W2982536526","https://openalex.org/W4380302312","https://openalex.org/W4385338604","https://openalex.org/W3081626085"],"abstract_inverted_index":{"Sports":[0],"injuries":[1,28],"of":[2,8,56,100],"high-level":[3],"athletes":[4],"restrict":[5],"the":[6,54,60,72,80,110,129,141,173],"improvement":[7],"sports":[9,18,27,40],"performance.":[10],"Under":[11],"this":[12,35],"premise,":[13],"an":[14],"efficient":[15],"and":[16,29,93,104,114,116,119],"accurate":[17],"injury":[19,31,41],"assessment":[20],"method":[21],"is":[22,74,125,154],"needed":[23],"to":[24,132,171],"detect":[25],"potential":[26],"conduct":[30],"prevention":[32],"training.":[33],"Therefore,":[34],"paper":[36],"proposes":[37],"a":[38,90,95,148,163],"novel":[39],"prediction":[42],"algorithm":[43,51,153],"based":[44],"on":[45,145,162],"visual":[46],"analysis":[47],"technology.":[48,107],"The":[49,66,85],"proposed":[50,174],"first":[52],"takes":[53],"time-frequency":[55],"sensed":[57,87],"data":[58,88,165],"as":[59],"convolutional":[61,101],"neural":[62,102],"network":[63],"(CNN)":[64],"input.":[65],"one-dimensional":[67,86],"time":[68],"series":[69],"collected":[70],"by":[71],"sensor":[73],"converted":[75],"into":[76],"two-dimensional":[77],"images":[78],"using":[79],"Gram":[81],"angle":[82],"domain":[83],"algorithm.":[84],"provides":[89,94],"new":[91],"perspective":[92],"basis":[96],"for":[97],"better":[98],"use":[99],"networks":[103],"computer":[105],"vision":[106],"Second,":[108],"combining":[109],"residual":[111,123],"network\u2019s":[112],"structure":[113],"advantages":[115],"hole":[117],"convolution":[118,121],"multihole":[120],"kernel":[122],"module":[124],"proposed.":[126,155],"It":[127],"improves":[128],"model\u2019s":[130],"ability":[131],"extract":[133],"features":[134],"at":[135],"different":[136],"scales":[137],"while":[138],"effectively":[139],"controlling":[140],"parameter":[142],"scale.":[143],"Based":[144],"these":[146],"modules,":[147],"single-sensor-based":[149],"athlete":[150],"action":[151],"recognition":[152],"Several":[156],"comparative":[157],"experiments":[158],"have":[159],"been":[160],"conducted":[161],"public":[164],"set":[166],"containing":[167],"only":[168],"acceleration":[169],"sensors":[170],"verify":[172],"algorithm\u2019s":[175],"effectiveness.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
