{"id":"https://openalex.org/W2089624101","doi":"https://doi.org/10.1145/2493988.2494325","title":"Confidence-based multiclass AdaBoost for physical activity monitoring","display_name":"Confidence-based multiclass AdaBoost for physical activity monitoring","publication_year":2013,"publication_date":"2013-09-08","ids":{"openalex":"https://openalex.org/W2089624101","doi":"https://doi.org/10.1145/2493988.2494325","mag":"2089624101"},"language":"en","primary_location":{"id":"doi:10.1145/2493988.2494325","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2493988.2494325","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 International Symposium on Wearable Computers","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-97524","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043824536","display_name":"Attila Reiss","orcid":null},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Attila Reiss","raw_affiliation_strings":["German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany"],"affiliations":[{"raw_affiliation_string":"German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany","institution_ids":["https://openalex.org/I33256026"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001137240","display_name":"Gustaf Hendeby","orcid":"https://orcid.org/0000-0002-1971-4295"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Gustaf Hendeby","raw_affiliation_strings":["Link\u00f6ping University, Link\u00f6ping, Sweden"],"affiliations":[{"raw_affiliation_string":"Link\u00f6ping University, Link\u00f6ping, Sweden","institution_ids":["https://openalex.org/I102134673"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051650277","display_name":"Didier Stricker","orcid":"https://orcid.org/0009-0004-8794-6858"},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Didier Stricker","raw_affiliation_strings":["German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany"],"affiliations":[{"raw_affiliation_string":"German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany","institution_ids":["https://openalex.org/I33256026"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5043824536"],"corresponding_institution_ids":["https://openalex.org/I33256026"],"apc_list":null,"apc_paid":null,"fwci":2.9937,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.92597226,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9984999895095825,"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":0.9984999895095825,"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/T10352","display_name":"Physical Activity and Health","score":0.965499997138977,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"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/T10866","display_name":"Nutritional Studies and Diet","score":0.9587000012397766,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.8908069729804993},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.8582311272621155},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7543227076530457},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7422463893890381},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7098506689071655},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6539312601089478},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.5224199295043945},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.500110387802124},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.4589058756828308},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"Multiclass classification","score":0.4214571714401245},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38481056690216064},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3628530204296112},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.2603868842124939}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8908069729804993},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.8582311272621155},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7543227076530457},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7422463893890381},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7098506689071655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6539312601089478},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.5224199295043945},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.500110387802124},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.4589058756828308},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.4214571714401245},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38481056690216064},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3628530204296112},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2603868842124939},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2493988.2494325","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2493988.2494325","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 International Symposium on Wearable Computers","raw_type":"proceedings-article"},{"id":"pmh:oai:DiVA.org:liu-97524","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-97524","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"}],"best_oa_location":{"id":"pmh:oai:DiVA.org:liu-97524","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-97524","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322568","display_name":"Stiftung Rheinland-Pfalz f\u00fcr Innovation","ror":"https://ror.org/01thcx676"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W98188630","https://openalex.org/W1563489020","https://openalex.org/W1578772208","https://openalex.org/W1966280301","https://openalex.org/W1968969471","https://openalex.org/W1988790447","https://openalex.org/W2024046085","https://openalex.org/W2026297770","https://openalex.org/W2030980398","https://openalex.org/W2032210760","https://openalex.org/W2060233269","https://openalex.org/W2063598276","https://openalex.org/W2089624101","https://openalex.org/W2093717447","https://openalex.org/W2095955281","https://openalex.org/W2097498700","https://openalex.org/W2124609194","https://openalex.org/W2124868070","https://openalex.org/W2144852094","https://openalex.org/W2164427779","https://openalex.org/W2401847728","https://openalex.org/W2483237440","https://openalex.org/W2487087946","https://openalex.org/W3120740533","https://openalex.org/W4244952642","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2327035729","https://openalex.org/W2348748958","https://openalex.org/W3039673966","https://openalex.org/W1538046993","https://openalex.org/W2884325279","https://openalex.org/W1570592793","https://openalex.org/W1525436954","https://openalex.org/W2385662756","https://openalex.org/W2585372724","https://openalex.org/W2241444561"],"abstract_inverted_index":{"Physical":[0],"activity":[1,88],"monitoring":[2],"has":[3],"recently":[4,104],"become":[5],"an":[6,87,91],"important":[7],"topic":[8],"in":[9],"wearable":[10],"computing,":[11],"motivated":[12],"by":[13],"e.g.":[14],"healthcare":[15],"applications.":[16],"However,":[17],"new":[18],"benchmark":[19,73],"results":[20,110],"show":[21],"that":[22,52,112],"the":[23,26,31,40,50,66,76,103,113,119,125],"difficulty":[24],"of":[25,33,49,99,124],"complex":[27,133],"classification":[28,120,134],"problems":[29],"exceeds":[30],"potential":[32],"existing":[34],"classifiers.":[35],"Therefore,":[36],"this":[37],"paper":[38],"proposes":[39],"ConfAdaBoost.M1":[41,115],"algorithm.":[42],"The":[43,61,108],"proposed":[44,114],"algorithm":[45,116],"is":[46,63,83],"a":[47,96],"variant":[48],"AdaBoost.M1":[51],"incorporates":[53],"well":[54],"established":[55],"ideas":[56],"for":[57,129],"confidence":[58],"based":[59],"boosting.":[60],"method":[62],"compared":[64],"to":[65],"most":[67,123],"commonly":[68],"used":[69],"boosting":[70],"methods":[71],"using":[72],"datasets":[74],"from":[75,102],"UCI":[77],"machine":[78],"learning":[79],"repository":[80],"and":[81,90,131],"it":[82],"also":[84],"evaluated":[85,126],"on":[86,122],"recognition":[89],"intensity":[92],"estimation":[93],"problem,":[94],"including":[95],"large":[97],"number":[98],"physical":[100],"activities":[101],"released":[105],"PAMAP2":[106],"dataset.":[107],"presented":[109],"indicate":[111],"significantly":[117],"improves":[118],"performance":[121],"datasets,":[127],"especially":[128],"larger":[130],"more":[132],"tasks.":[135]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}