{"id":"https://openalex.org/W3200564239","doi":"https://doi.org/10.1155/2021/6232968","title":"Method of Analyzing and Managing Volleyball Action by Using Action Sensor of Mobile Device","display_name":"Method of Analyzing and Managing Volleyball Action by Using Action Sensor of Mobile Device","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3200564239","doi":"https://doi.org/10.1155/2021/6232968","mag":"3200564239"},"language":"en","primary_location":{"id":"doi:10.1155/2021/6232968","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/6232968","pdf_url":"https://downloads.hindawi.com/journals/js/2021/6232968.pdf","source":{"id":"https://openalex.org/S96783963","display_name":"Journal of Sensors","issn_l":"1687-725X","issn":["1687-725X","1687-7268"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869","https://openalex.org/P4310320595"],"host_organization_lineage_names":["Hindawi Publishing Corporation","Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Sensors","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/js/2021/6232968.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101714454","display_name":"Xu Sun","orcid":"https://orcid.org/0000-0002-8500-8225"},"institutions":[{"id":"https://openalex.org/I4210158810","display_name":"Shenyang Sport University","ror":"https://ror.org/05kz0b404","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210158810"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Sun","raw_affiliation_strings":["Volleyball Teaching and Research Section, Shenyang Sport University, Shenyang, 110000 Liaoning, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Volleyball Teaching and Research Section, Shenyang Sport University, Shenyang, 110000 Liaoning, China","institution_ids":["https://openalex.org/I4210158810"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066909470","display_name":"Kai Zhao","orcid":"https://orcid.org/0000-0002-5448-9919"},"institutions":[{"id":"https://openalex.org/I87710204","display_name":"Beijing Sport University","ror":"https://ror.org/03w0k0x36","country_code":"CN","type":"education","lineage":["https://openalex.org/I87710204"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kai Zhao","raw_affiliation_strings":["China Volleyball College, Beijing Sport University, Beijing, 100089 Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5448-9919","affiliations":[{"raw_affiliation_string":"China Volleyball College, Beijing Sport University, Beijing, 100089 Beijing, China","institution_ids":["https://openalex.org/I87710204"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001456655","display_name":"Wei Jiang","orcid":"https://orcid.org/0000-0001-5459-1510"},"institutions":[{"id":"https://openalex.org/I87710204","display_name":"Beijing Sport University","ror":"https://ror.org/03w0k0x36","country_code":"CN","type":"education","lineage":["https://openalex.org/I87710204"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Jiang","raw_affiliation_strings":["China Volleyball College, Beijing Sport University, Beijing, 100089 Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Volleyball College, Beijing Sport University, Beijing, 100089 Beijing, China","institution_ids":["https://openalex.org/I87710204"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075242952","display_name":"Xinlong Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinlong Jin","raw_affiliation_strings":["Academic Affairs Office, Dalian University of Science and Technology, Dalian, 116000 Liaoning, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academic Affairs Office, Dalian University of Science and Technology, Dalian, 116000 Liaoning, China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5066909470"],"corresponding_institution_ids":["https://openalex.org/I87710204"],"apc_list":{"value":2830,"currency":"USD","value_usd":2830},"apc_paid":{"value":2830,"currency":"USD","value_usd":2830},"fwci":0.3659,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.56924871,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"2021","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.97079998254776,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.97079998254776,"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/T13647","display_name":"AI and Big Data Applications","score":0.9503999948501587,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9491999745368958,"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/support-vector-machine","display_name":"Support vector machine","score":0.6455498933792114},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6410757303237915},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5881921052932739},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.510228157043457},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5073253512382507},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4535754919052124},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45106345415115356},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4490549862384796},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.42652803659439087},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3571428656578064}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6455498933792114},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6410757303237915},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5881921052932739},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.510228157043457},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5073253512382507},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4535754919052124},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45106345415115356},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4490549862384796},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.42652803659439087},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3571428656578064},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1155/2021/6232968","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/6232968","pdf_url":"https://downloads.hindawi.com/journals/js/2021/6232968.pdf","source":{"id":"https://openalex.org/S96783963","display_name":"Journal of Sensors","issn_l":"1687-725X","issn":["1687-725X","1687-7268"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869","https://openalex.org/P4310320595"],"host_organization_lineage_names":["Hindawi Publishing Corporation","Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Sensors","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:4e730d97084e495fb01dd5702947ce7e","is_oa":false,"landing_page_url":"https://doaj.org/article/4e730d97084e495fb01dd5702947ce7e","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Sensors, Vol 2021 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2021/6232968","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/6232968","pdf_url":"https://downloads.hindawi.com/journals/js/2021/6232968.pdf","source":{"id":"https://openalex.org/S96783963","display_name":"Journal of Sensors","issn_l":"1687-725X","issn":["1687-725X","1687-7268"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869","https://openalex.org/P4310320595"],"host_organization_lineage_names":["Hindawi Publishing Corporation","Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3200564239.pdf","grobid_xml":"https://content.openalex.org/works/W3200564239.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W2072419079","https://openalex.org/W2198557826","https://openalex.org/W2295938624","https://openalex.org/W2304098014","https://openalex.org/W2307856135","https://openalex.org/W2313342918","https://openalex.org/W2318477679","https://openalex.org/W2343546746","https://openalex.org/W2416407175","https://openalex.org/W2527826171","https://openalex.org/W2539157886","https://openalex.org/W2549486930","https://openalex.org/W2561209028","https://openalex.org/W2588605926","https://openalex.org/W2592405550","https://openalex.org/W2592630360","https://openalex.org/W2617336958","https://openalex.org/W2735399951","https://openalex.org/W2736614725","https://openalex.org/W2742615025","https://openalex.org/W2745590804","https://openalex.org/W2771488283","https://openalex.org/W2784216502","https://openalex.org/W2963349810","https://openalex.org/W2963603009","https://openalex.org/W3022634362","https://openalex.org/W3159912878","https://openalex.org/W3166866321","https://openalex.org/W7034612288"],"related_works":["https://openalex.org/W2091018038","https://openalex.org/W2225378543","https://openalex.org/W9839718","https://openalex.org/W3110613631","https://openalex.org/W4287122200","https://openalex.org/W2742744817","https://openalex.org/W2040913503","https://openalex.org/W3166845860","https://openalex.org/W3202472720","https://openalex.org/W2393010104"],"abstract_inverted_index":{"With":[0],"the":[1,21,45,65,99,107,117,125,133,144,155,158,162,168,174,180,188,193,196,210,221,249,256,271,314,322,326,332,340,344,356,367,374],"development":[2],"of":[3,23,47,55,67,101,109,120,129,137,149,195,213,239,262,275,325,343,370],"electronic":[4,13],"technology":[5],"and":[6,10,63,69,76,111,147,192,265,331,337,349,373],"sensor":[7,119,327],"technology,":[8],"more":[9,11,96,267],"intelligent":[12],"devices":[14,243,280],"integrate":[15],"micro":[16],"inertial":[17],"sensors,":[18],"which":[19,50,80,171,288],"makes":[20],"research":[22,42],"human":[24,231,240,296],"action":[25,29,37,56,114,118,319],"recognition":[26,38,89,127,135,175,222,238,299,368,375],"based":[27,90,300,359],"on":[28,91,124,301,360],"sensing":[30],"data":[31,57,145,189,257,292],"have":[32],"great":[33],"application":[34,268],"value.":[35],"Data\u2010based":[36],"is":[39,51,81,141,185,199,217,285,310,328,334,347,377],"a":[40,53,259,290],"new":[41],"direction":[43],"in":[44,83,154],"field":[46],"pattern":[48,298],"recognition,":[49,64],"essentially":[52],"process":[54,66,136,198],"acquisition,":[58],"feature":[59,61],"extraction,":[60,62],"classification":[68,159,190,197,315],"recognition.":[70],"Inertial":[71],"motion":[72,88,126,134,228,250,277,283,297,302],"information":[73,284],"includes":[74],"acceleration":[75],"angular":[77],"velocity":[78],"information,":[79,93],"ubiquitous":[82],"daily":[84],"life.":[85],"Compared":[86],"with":[87,318],"visual":[92],"it":[94],"can":[95,364],"directly":[97,172],"reflect":[98],"meaning":[100],"action.":[102],"This":[103,273],"study":[104],"mainly":[105],"discusses":[106],"method":[108,274,294,358],"analyzing":[110],"managing":[112],"volleyball":[113,150,371],"by":[115,201],"using":[116],"mobile":[121,242],"device.":[122,272],"Based":[123],"algorithm":[128,160,184,309,316],"support":[130,138,181,306],"vector":[131,139,182,307],"machine,":[132],"machine":[140,183,308],"constructed.":[142],"When":[143,321],"terminal":[146],"gateway":[148],"players":[151],"are":[152],"not":[153],"same":[156],"LAN,":[157],"classifies":[161],"samples":[163],"to":[164,219,226,230,235,245,248,281,312],"be":[165],"tested":[166],"through":[167],"characteristic":[169],"data,":[170,252],"affects":[173],"results.":[176],"In":[177,233],"this":[178],"paper,":[179],"selected":[186],"as":[187],"algorithm,":[191],"calculation":[194],"reduced":[200],"designing":[202],"an":[203],"appropriate":[204],"kernel":[205,362],"function.":[206],"For":[207],"multiclass":[208],"problems,":[209],"hierarchical":[211],"structure":[212],"directed":[214],"acyclic":[215],"graph":[216],"optimized":[218],"improve":[220,366],"rate.":[223],"We":[224],"need":[225,244],"bind":[227],"sensors":[229,278],"joints.":[232],"order":[234],"realize":[236],"real\u2010time":[237],"motion,":[241],"add":[246],"windows":[247],"capture":[251],"that":[253,355],"is,":[254],"divide":[255],"into":[258,279],"small":[260],"sequence":[261],"specified":[263],"length,":[264],"provide":[266],"scenarios":[269],"for":[270,295],"embedding":[276],"read":[282],"widely":[286],"used,":[287],"provides":[289],"convenient":[291],"acquisition":[293],"information.":[303],"The":[304,352],"multiclassification":[305],"used":[311],"train":[313],"model":[317],"data.":[320],"signal":[323],"strength":[324],"90":[329],"t":[330],"speed":[333],"2.0":[335],"m/s":[336],"0.5":[338],"m/s,":[339],"detection":[341],"accuracy":[342,369],"adaptive":[345],"threshold":[346],"93%":[348],"95%,":[350],"respectively.":[351],"results":[353],"show":[354],"SVM":[357],"hybrid":[361],"function":[363],"greatly":[365],"stroke,":[372],"time":[376],"short.":[378]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
