{"id":"https://openalex.org/W2040474274","doi":"https://doi.org/10.3390/e15041375","title":"Classification of Knee Joint Vibration Signals Using Bivariate Feature Distribution Estimation and Maximal Posterior Probability Decision Criterion","display_name":"Classification of Knee Joint Vibration Signals Using Bivariate Feature Distribution Estimation and Maximal Posterior Probability Decision Criterion","publication_year":2013,"publication_date":"2013-04-17","ids":{"openalex":"https://openalex.org/W2040474274","doi":"https://doi.org/10.3390/e15041375","mag":"2040474274"},"language":"en","primary_location":{"id":"doi:10.3390/e15041375","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e15041375","pdf_url":"https://www.mdpi.com/1099-4300/15/4/1375/pdf?version=1424785012","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/15/4/1375/pdf?version=1424785012","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007483809","display_name":"Yunfeng Wu","orcid":"https://orcid.org/0000-0002-3612-7818"},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yunfeng Wu","raw_affiliation_strings":["School of Information Science and Technology, Xiamen University, 422 Si Ming South Road,Xiamen 361005, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Xiamen University, 422 Si Ming South Road,Xiamen 361005, China","institution_ids":["https://openalex.org/I75867142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029489476","display_name":"Suxian Cai","orcid":"https://orcid.org/0000-0003-1900-8929"},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Suxian Cai","raw_affiliation_strings":["School of Information Science and Technology, Xiamen University, 422 Si Ming South Road,Xiamen 361005, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Xiamen University, 422 Si Ming South Road,Xiamen 361005, China","institution_ids":["https://openalex.org/I75867142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108298708","display_name":"Shanshan Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanshan Yang","raw_affiliation_strings":["School of Information Science and Technology, Xiamen University, 422 Si Ming South Road,Xiamen 361005, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Xiamen University, 422 Si Ming South Road,Xiamen 361005, China","institution_ids":["https://openalex.org/I75867142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041679034","display_name":"Fang Zheng","orcid":"https://orcid.org/0000-0002-7858-4080"},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Zheng","raw_affiliation_strings":["School of Information Science and Technology, Xiamen University, 422 Si Ming South Road,Xiamen 361005, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Xiamen University, 422 Si Ming South Road,Xiamen 361005, China","institution_ids":["https://openalex.org/I75867142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023598657","display_name":"Ning Xiang","orcid":"https://orcid.org/0000-0003-4225-1775"},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Xiang","raw_affiliation_strings":["School of Information Science and Technology, Xiamen University, 422 Si Ming South Road,Xiamen 361005, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Xiamen University, 422 Si Ming South Road,Xiamen 361005, China","institution_ids":["https://openalex.org/I75867142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5007483809"],"corresponding_institution_ids":["https://openalex.org/I75867142"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":4.0333,"has_fulltext":false,"cited_by_count":49,"citation_normalized_percentile":{"value":0.93421978,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"15","issue":"4","first_page":"1375","last_page":"1387"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10105","display_name":"Osteoarthritis Treatment and Mechanisms","score":0.973800003528595,"subfield":{"id":"https://openalex.org/subfields/2745","display_name":"Rheumatology"},"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/T10105","display_name":"Osteoarthritis Treatment and Mechanisms","score":0.973800003528595,"subfield":{"id":"https://openalex.org/subfields/2745","display_name":"Rheumatology"},"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/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9671000242233276,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T10784","display_name":"Muscle activation and electromyography studies","score":0.9660999774932861,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/joint-probability-distribution","display_name":"Joint probability distribution","score":0.7346595525741577},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6861207485198975},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.634267270565033},{"id":"https://openalex.org/keywords/bivariate-analysis","display_name":"Bivariate analysis","score":0.621330201625824},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.6099031567573547},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6087214946746826},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5616318583488464},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5552856922149658},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.553903341293335},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5026383399963379},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.49130621552467346},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.44939759373664856},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4487098157405853},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.43196558952331543},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.41404691338539124},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3963261842727661},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.20996564626693726}],"concepts":[{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.7346595525741577},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6861207485198975},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.634267270565033},{"id":"https://openalex.org/C64341305","wikidata":"https://www.wikidata.org/wiki/Q4919225","display_name":"Bivariate analysis","level":2,"score":0.621330201625824},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.6099031567573547},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6087214946746826},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5616318583488464},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5552856922149658},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.553903341293335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5026383399963379},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.49130621552467346},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.44939759373664856},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4487098157405853},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.43196558952331543},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.41404691338539124},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3963261842727661},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.20996564626693726},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/e15041375","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e15041375","pdf_url":"https://www.mdpi.com/1099-4300/15/4/1375/pdf?version=1424785012","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:43a2a10865994aad9a763cc1798d707f","is_oa":true,"landing_page_url":"https://doaj.org/article/43a2a10865994aad9a763cc1798d707f","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 15, Iss 4, Pp 1375-1387 (2013)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/15/4/1375/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e15041375","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy; Volume 15; Issue 4; Pages: 1375-1387","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e15041375","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e15041375","pdf_url":"https://www.mdpi.com/1099-4300/15/4/1375/pdf?version=1424785012","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6700000166893005,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2040474274.pdf","grobid_xml":"https://content.openalex.org/works/W2040474274.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W631502863","https://openalex.org/W1496317909","https://openalex.org/W1517089960","https://openalex.org/W1970446753","https://openalex.org/W1975882756","https://openalex.org/W1990454287","https://openalex.org/W1999764646","https://openalex.org/W2001619934","https://openalex.org/W2005874536","https://openalex.org/W2017299800","https://openalex.org/W2024770626","https://openalex.org/W2088344044","https://openalex.org/W2096141536","https://openalex.org/W2099245131","https://openalex.org/W2100155524","https://openalex.org/W2106320830","https://openalex.org/W2106466306","https://openalex.org/W2118020555","https://openalex.org/W2119821739","https://openalex.org/W2128392253","https://openalex.org/W2132549764","https://openalex.org/W2134262590","https://openalex.org/W2148603752","https://openalex.org/W2152999428","https://openalex.org/W2161907315","https://openalex.org/W2169971029","https://openalex.org/W2332757517","https://openalex.org/W2476797758","https://openalex.org/W2583488070","https://openalex.org/W2799061466","https://openalex.org/W4239510810","https://openalex.org/W6674890453"],"related_works":["https://openalex.org/W1528102763","https://openalex.org/W2465871978","https://openalex.org/W2351755528","https://openalex.org/W2585385340","https://openalex.org/W4297926828","https://openalex.org/W132006996","https://openalex.org/W871299571","https://openalex.org/W1569550976","https://openalex.org/W2102345963","https://openalex.org/W3003818300"],"abstract_inverted_index":{"Analysis":[0],"of":[1,23,35,45,65,82,89,145,151,194,203,212],"knee":[2,36,76,213],"joint":[3,37,77,214],"vibration":[4],"or":[5,177],"vibroarthrographic":[6],"(VAG)":[7],"signals":[8,39,68,85],"using":[9,112],"signal":[10,94,107],"processing":[11],"and":[12,73,92,124,147,200],"machine":[13,120,181],"learning":[14],"algorithms":[15],"possesses":[16],"high":[17],"potential":[18],"for":[19,210],"the":[20,42,50,55,63,66,83,90,98,102,113,125,141,148,154,163,168,178,192,195,201,204],"noninvasive":[21],"detection":[22],"articular":[24,47],"cartilage":[25],"degeneration,":[26],"which":[27,159],"may":[28],"reduce":[29],"unnecessary":[30],"exploratory":[31],"surgery.":[32],"Feature":[33],"representation":[34],"VAG":[38,67,84,215],"helps":[40],"characterize":[41],"pathological":[43],"condition":[44],"degenerative":[46],"cartilages":[48],"in":[49,101],"knee.":[51],"This":[52],"paper":[53],"used":[54],"kernel-based":[56],"probability":[57,128,134,207],"density":[58],"estimation":[59,199],"method":[60],"to":[61,139,162],"model":[62],"distributions":[64,88],"recorded":[69],"from":[70],"healthy":[71],"subjects":[72],"patients":[74],"with":[75,97,121,182],"disorders.":[78],"The":[79,106,131],"estimated":[80],"densities":[81],"showed":[86],"explicit":[87],"normal":[91],"abnormal":[93],"groups,":[95],"along":[96],"corresponding":[99],"contours":[100],"bivariate":[103,196],"feature":[104,197],"space.":[105],"classifications":[108],"were":[109,160],"performed":[110],"by":[111,166],"Fisher\u2019s":[114,169],"linear":[115,170],"discriminant":[116,171],"analysis,":[117],"support":[118,179],"vector":[119,180],"polynomial":[122,183],"kernels,":[123],"maximal":[126,132,205],"posterior":[127,133,206],"decision":[129,135,208],"criterion.":[130],"criterion":[136,209],"was":[137],"able":[138],"provide":[140],"total":[142],"classification":[143],"accuracy":[144],"86.67%":[146],"area":[149],"(Az)":[150],"0.9096":[152],"under":[153],"receiver":[155],"operating":[156],"characteristics":[157],"curve,":[158],"superior":[161],"results":[164,190],"obtained":[165],"either":[167],"analysis":[172,211],"(accuracy:":[173,185],"81.33%,":[174,186],"Az:":[175,187],"0.8564)":[176],"kernels":[184],"0.8533).":[188],"Such":[189],"demonstrated":[191],"merits":[193],"distribution":[198],"superiority":[202],"signals.":[216]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":10}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
