{"id":"https://openalex.org/W2294147839","doi":"https://doi.org/10.1109/embc.2015.7319532","title":"A Random Forest-based ensemble method for activity recognition","display_name":"A Random Forest-based ensemble method for activity recognition","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W2294147839","doi":"https://doi.org/10.1109/embc.2015.7319532","mag":"2294147839","pmid":"https://pubmed.ncbi.nlm.nih.gov/26737432"},"language":"en","primary_location":{"id":"doi:10.1109/embc.2015.7319532","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2015.7319532","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","pubmed"],"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/A5007397903","display_name":"Zengtao Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zengtao Feng","raw_affiliation_strings":["School of Instrument Science and Engineering, Southeast University, Nanjing, Jiangsu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Instrument Science and Engineering, Southeast University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026383998","display_name":"Lingfei Mo","orcid":"https://orcid.org/0000-0002-8561-9122"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingfei Mo","raw_affiliation_strings":["School of Instrument Science and Engineering, Southeast University, Nanjing, Jiangsu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Instrument Science and Engineering, Southeast University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027120547","display_name":"Meng Li","orcid":"https://orcid.org/0000-0002-9470-9787"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Li","raw_affiliation_strings":["School of Instrument Science and Engineering, Southeast University, Nanjing, Jiangsu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Instrument Science and Engineering, Southeast University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":1.7565,"has_fulltext":false,"cited_by_count":110,"citation_normalized_percentile":{"value":0.92546304,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"2015","issue":null,"first_page":"5074","last_page":"5077"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9993000030517578,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9993000030517578,"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/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9588000178337097,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.9455167055130005},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7595441341400146},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.7136680483818054},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6653171181678772},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6459031105041504},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6250394582748413},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5482429265975952},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.46487855911254883},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4496590793132782},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.4200695753097534},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3403809070587158}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.9455167055130005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7595441341400146},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.7136680483818054},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6653171181678772},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6459031105041504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6250394582748413},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5482429265975952},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.46487855911254883},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4496590793132782},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.4200695753097534},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3403809070587158}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009068","descriptor_name":"Movement","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009068","descriptor_name":"Movement","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009068","descriptor_name":"Movement","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc.2015.7319532","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2015.7319532","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:26737432","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26737432","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.7200000286102295}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1930624869","https://openalex.org/W1975428667","https://openalex.org/W1990104191","https://openalex.org/W2013582641","https://openalex.org/W2018608640","https://openalex.org/W2023302299","https://openalex.org/W2026297770","https://openalex.org/W2091313930","https://openalex.org/W2132691216","https://openalex.org/W2164041372","https://openalex.org/W2227813149","https://openalex.org/W2498672755","https://openalex.org/W2911964244","https://openalex.org/W6640462745","https://openalex.org/W6643977797","https://openalex.org/W6689489409"],"related_works":["https://openalex.org/W2811014843","https://openalex.org/W2944292463","https://openalex.org/W3014252901","https://openalex.org/W2188759683","https://openalex.org/W4317376680","https://openalex.org/W4360777922","https://openalex.org/W4401361218","https://openalex.org/W2034680797","https://openalex.org/W2967426019","https://openalex.org/W3210752578"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,37,67],"multi-sensor":[4],"ensemble":[5,19,106],"approach":[6],"to":[7,35,74,87],"human":[8,46],"physical":[9],"activity":[10,47],"(PA)":[11],"recognition,":[12],"using":[13],"random":[14],"forest.":[15],"We":[16],"designed":[17],"an":[18,94],"learning":[20],"algorithm,":[21,52],"which":[22,65],"integrates":[23],"several":[24],"independent":[25],"Random":[26],"Forest":[27],"classifiers":[28],"based":[29,109],"on":[30,110],"different":[31],"sensor":[32],"feature":[33],"sets":[34],"build":[36],"more":[38,40],"stable,":[39],"accurate":[41],"and":[42,76,121],"faster":[43,102],"classifier":[44,107],"for":[45,62],"recognition.":[48],"To":[49],"evaluate":[50],"the":[51,57,83,99,111],"PA":[53,91],"data":[54],"collected":[55],"from":[56],"PAMAP":[58],"(Physical":[59],"Activity":[60],"Monitoring":[61],"Aging":[63],"People),":[64],"is":[66,85,101],"standard,":[68],"publicly":[69],"available":[70],"database,":[71],"was":[72],"utilized":[73],"train":[75],"test.":[77],"The":[78,105],"experimental":[79],"results":[80],"show":[81],"that":[82],"algorithm":[84,115],"able":[86],"correctly":[88],"recognize":[89],"19":[90],"types":[92],"with":[93],"accuracy":[95,120],"of":[96],"93.44%,":[97],"while":[98],"training":[100],"than":[103],"others.":[104],"system":[108],"RF":[112],"(Random":[113],"Forest)":[114],"can":[116],"achieve":[117],"high":[118],"recognition":[119],"fast":[122],"calculation.":[123]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":18},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2025-10-10T00:00:00"}