{"id":"https://openalex.org/W4407775720","doi":"https://doi.org/10.1145/3711129.3711147","title":"Research on muscle fatigue classification based on principal component analysis-random forest algorithm","display_name":"Research on muscle fatigue classification based on principal component analysis-random forest algorithm","publication_year":2024,"publication_date":"2024-10-18","ids":{"openalex":"https://openalex.org/W4407775720","doi":"https://doi.org/10.1145/3711129.3711147"},"language":"en","primary_location":{"id":"doi:10.1145/3711129.3711147","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3711129.3711147","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 8th International Conference on Electronic Information Technology and Computer Engineering","raw_type":"proceedings-article"},"type":"article","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/A5066110142","display_name":"Peng Pang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135466","display_name":"Heilongjiang University of Technology","ror":"https://ror.org/03r2nz980","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210135466"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peng Pang","raw_affiliation_strings":["College of Electrical and Information Engineering, Heilongjiang University of Technology, Jixi, Heilongjiang, China"],"raw_orcid":"https://orcid.org/0009-0001-7534-2465","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Heilongjiang University of Technology, Jixi, Heilongjiang, China","institution_ids":["https://openalex.org/I4210135466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109243381","display_name":"Leilei Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135466","display_name":"Heilongjiang University of Technology","ror":"https://ror.org/03r2nz980","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210135466"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leilei Tang","raw_affiliation_strings":["College of Electrical and Information Engineering, Heilongjiang University of Technology, Jixi, Heilongjiang, China"],"raw_orcid":"https://orcid.org/0009-0003-4293-9817","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Heilongjiang University of Technology, Jixi, Heilongjiang, China","institution_ids":["https://openalex.org/I4210135466"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5066110142"],"corresponding_institution_ids":["https://openalex.org/I4210135466"],"apc_list":null,"apc_paid":null,"fwci":0.1767,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50777978,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"91","last_page":"96"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.967199981212616,"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"}},"topics":[{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.967199981212616,"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"}},{"id":"https://openalex.org/T12006","display_name":"Ergonomics and Musculoskeletal Disorders","score":0.9402999877929688,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.8555819988250732},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.8212206363677979},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.618952751159668},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5658655166625977},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.5209580659866333},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4681691527366638},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4454098641872406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4041399359703064},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3492203652858734},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.058352112770080566}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.8555819988250732},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.8212206363677979},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.618952751159668},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5658655166625977},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.5209580659866333},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4681691527366638},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4454098641872406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4041399359703064},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3492203652858734},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.058352112770080566},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3711129.3711147","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3711129.3711147","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 8th International Conference on Electronic Information Technology and Computer Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2161490686","https://openalex.org/W3046303135","https://openalex.org/W4312565078"],"related_works":["https://openalex.org/W4401361218","https://openalex.org/W2034680797","https://openalex.org/W2967426019","https://openalex.org/W3210752578","https://openalex.org/W2990537558","https://openalex.org/W4207040723","https://openalex.org/W4200492042","https://openalex.org/W2621610018","https://openalex.org/W2601142304","https://openalex.org/W4300960428"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,80,111,145],"solve":[3],"the":[4,36,46,81,87,104,113,116,126,128,132,149,157,164],"problem":[5],"of":[6,9,26,92,115,131,166],"low":[7],"accuracy":[8,130],"muscle":[10,167],"fatigue":[11,18],"classification":[12,19,129,165],"using":[13],"surface":[14,27,37],"electromyography":[15,28],"(sEMG),":[16],"a":[17],"model":[20,82],"based":[21,136],"on":[22,137],"principal":[23,71,138],"component":[24,58,139],"analysis":[25,59,140],"and":[29,44,51,75,106],"random":[30,93,133,151],"forest":[31,94,134,152],"algorithm":[32,135],"was":[33,63],"proposed.":[34],"Firstly,":[35],"EMG":[38],"signal":[39],"is":[40,141],"pre-processed":[41],"by":[42,143],"de-noising,":[43],"then":[45],"time":[47],"domain,":[48],"frequency":[49],"domain":[50,53],"time-frequency":[52],"features":[54,76],"are":[55],"extracted.":[56],"Principal":[57],"in":[60,163],"feature":[61,66,99],"extraction":[62],"used":[64],"for":[65],"dimensionality":[67],"reduction,":[68],"three":[69],"effective":[70],"components":[72],"were":[73,83,101,109],"extracted,":[74],"with":[77,86,148],"high":[78],"contribution":[79],"screened":[84,97],"combined":[85],"variable":[88],"importance":[89],"ranking":[90],"results":[91,121],"algorithm.":[95],"The":[96,119],"joint":[98],"parameters":[100],"input":[102],"into":[103],"classifier,":[105],"8":[107],"subjects":[108],"tested":[110],"verify":[112],"rationality":[114],"proposed":[117,158],"method.":[118],"experimental":[120],"showed":[122],"that:":[123],"By":[124],"optimizing":[125],"parameters,":[127],"increased":[142],"5%":[144],"93.3%":[146],"compared":[147],"simple":[150],"algorithm,":[153],"which":[154],"proves":[155],"that":[156],"method":[159],"has":[160],"excellent":[161],"effect":[162],"fatigue.":[168]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}