{"id":"https://openalex.org/W2889741183","doi":"https://doi.org/10.1145/3243082.3243116","title":"Human Activity Recognition on Smartphones using Symbolic Data Representation","display_name":"Human Activity Recognition on Smartphones using Symbolic Data Representation","publication_year":2018,"publication_date":"2018-09-19","ids":{"openalex":"https://openalex.org/W2889741183","doi":"https://doi.org/10.1145/3243082.3243116","mag":"2889741183"},"language":"en","primary_location":{"id":"doi:10.1145/3243082.3243116","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3243082.3243116","pdf_url":null,"source":null,"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th Brazilian Symposium on Multimedia and the Web","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/A5005261184","display_name":"Kevin G. Montero Quispe","orcid":"https://orcid.org/0000-0002-0550-4748"},"institutions":[{"id":"https://openalex.org/I62885914","display_name":"Universidade Federal do Amazonas","ror":"https://ror.org/02263ky35","country_code":"BR","type":"education","lineage":["https://openalex.org/I62885914"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Kevin G. Montero Quispe","raw_affiliation_strings":["Universidade Federal do Amazonas, Instituto de Computa\u00e7\u00e3o, Manaus, Amazonas"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade Federal do Amazonas, Instituto de Computa\u00e7\u00e3o, Manaus, Amazonas","institution_ids":["https://openalex.org/I62885914"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037006717","display_name":"Wesllen Sousa Lima","orcid":"https://orcid.org/0000-0001-9669-1659"},"institutions":[{"id":"https://openalex.org/I62885914","display_name":"Universidade Federal do Amazonas","ror":"https://ror.org/02263ky35","country_code":"BR","type":"education","lineage":["https://openalex.org/I62885914"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Wesllen Sousa Lima","raw_affiliation_strings":["Universidade Federal do Amazonas, Instituto de Computa\u00e7\u00e3o, Manaus, Amazonas"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade Federal do Amazonas, Instituto de Computa\u00e7\u00e3o, Manaus, Amazonas","institution_ids":["https://openalex.org/I62885914"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033286636","display_name":"Eduardo Souto","orcid":"https://orcid.org/0000-0003-0003-908X"},"institutions":[{"id":"https://openalex.org/I62885914","display_name":"Universidade Federal do Amazonas","ror":"https://ror.org/02263ky35","country_code":"BR","type":"education","lineage":["https://openalex.org/I62885914"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Eduardo J. Pereira Souto","raw_affiliation_strings":["Universidade Federal do Amazonas, Instituto de Computa\u00e7\u00e3o, Manaus, Amazonas"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade Federal do Amazonas, Instituto de Computa\u00e7\u00e3o, Manaus, Amazonas","institution_ids":["https://openalex.org/I62885914"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.212,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.55951511,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"93","last_page":"100"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9998000264167786,"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":0.9998000264167786,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9873999953269958,"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/activity-recognition","display_name":"Activity recognition","score":0.8193225860595703},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8027052879333496},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.7405457496643066},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5789143443107605},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5744500160217285},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5479738712310791},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5457051396369934},{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.5266596674919128},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5110663175582886},{"id":"https://openalex.org/keywords/boss","display_name":"Boss","score":0.4830211102962494},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.4586924910545349},{"id":"https://openalex.org/keywords/wearable-technology","display_name":"Wearable technology","score":0.44108492136001587},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41331109404563904},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34072619676589966}],"concepts":[{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.8193225860595703},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8027052879333496},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.7405457496643066},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5789143443107605},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5744500160217285},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5479738712310791},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5457051396369934},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.5266596674919128},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5110663175582886},{"id":"https://openalex.org/C2777020290","wikidata":"https://www.wikidata.org/wiki/Q4947493","display_name":"Boss","level":2,"score":0.4830211102962494},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.4586924910545349},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.44108492136001587},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41331109404563904},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34072619676589966},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3243082.3243116","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3243082.3243116","pdf_url":null,"source":null,"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th Brazilian Symposium on Multimedia and the Web","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W22482183","https://openalex.org/W82044129","https://openalex.org/W134960717","https://openalex.org/W1757644187","https://openalex.org/W1964842249","https://openalex.org/W1968354112","https://openalex.org/W2016944175","https://openalex.org/W2017634428","https://openalex.org/W2023302299","https://openalex.org/W2026909728","https://openalex.org/W2046766629","https://openalex.org/W2054242744","https://openalex.org/W2054780155","https://openalex.org/W2076068958","https://openalex.org/W2097575504","https://openalex.org/W2121232806","https://openalex.org/W2129793335","https://openalex.org/W2164274563","https://openalex.org/W2165612380","https://openalex.org/W2171694978","https://openalex.org/W2237307454","https://openalex.org/W2341105960","https://openalex.org/W2550476060","https://openalex.org/W2555209581","https://openalex.org/W2594116048","https://openalex.org/W2612445135","https://openalex.org/W2748565338","https://openalex.org/W2759690896","https://openalex.org/W2761268027","https://openalex.org/W2765748065","https://openalex.org/W2789868604","https://openalex.org/W2795342689","https://openalex.org/W4240007298","https://openalex.org/W4242867944"],"related_works":["https://openalex.org/W3210524396","https://openalex.org/W1996775904","https://openalex.org/W2136244850","https://openalex.org/W1496945489","https://openalex.org/W2092774949","https://openalex.org/W3007787046","https://openalex.org/W2384794170","https://openalex.org/W2376068818","https://openalex.org/W135799652","https://openalex.org/W2582769230"],"abstract_inverted_index":{"In":[0,36],"ubiquitous":[1],"computing,":[2],"Human":[3],"Activity":[4],"Recognition":[5],"(HAR)":[6],"systems":[7],"have":[8,57],"an":[9],"important":[10],"role":[11],"to":[12,76,114,120,128],"enabled":[13],"continuous":[14],"monitoring":[15,28],"of":[16,45,98],"human":[17,106],"behavior.":[18],"This":[19],"technology":[20],"can":[21,125],"be":[22,126],"useful":[23],"in":[24,118],"healthcare":[25],"applications,":[26],"for":[27,51,91,161],"patients'":[29],"health":[30],"and":[31,53,141,163,178,180],"encourage":[32],"a":[33,46,88,185],"healthy":[34],"lifestyle.":[35],"this":[37,84],"paper,":[38],"we":[39,86],"focus":[40],"on":[41,69,94,152],"features":[42,61,104,148],"extraction":[43],"stage":[44],"HAR":[47,56,92],"system.":[48],"Many":[49],"studies":[50],"mobile":[52],"wearable":[54],"sensor-based":[55],"applied":[58],"manually":[59],"engineered":[60],"that":[62,101,122,169],"need":[63],"domain":[64],"expert":[65],"knowledge.":[66],"However,":[67],"trust":[68],"such":[70],"knowledge":[71],"is":[72,112,149],"problematic":[73],"when":[74],"aiming":[75],"generalize":[77],"across":[78,176],"different":[79],"application":[80],"domains.":[81],"To":[82],"overcome":[83],"problem,":[85],"present":[87],"novel":[89],"approach":[90],"based":[93],"symbolic":[95,123],"data":[96,154],"representation":[97,124],"time":[99,116],"series":[100],"extract":[102],"structural":[103],"without":[105],"efforts.":[107],"The":[108,166],"Bag-Of-SFA-Symbols":[109],"(BOSS)":[110],"method":[111,140,171],"extended":[113],"multi-dimensional":[115],"series,":[117],"order":[119],"enable":[121],"used":[127],"process":[129],"the":[130,138],"inertial":[131],"sensors":[132],"data.":[133],"A":[134],"comparative":[135],"study":[136],"between":[137],"proposed":[139],"four":[142],"machine":[143],"learning":[144],"classifiers":[145],"with":[146],"handcraft":[147],"presented.":[150],"Experiments":[151],"accelerometer":[153],"from":[155],"three":[156],"publicly":[157],"datasets":[158,177],"were":[159],"executed":[160],"subject-dependent":[162],"subject-independent":[164],"evaluation.":[165],"results":[167],"show":[168],"our":[170],"achieves":[172],"good":[173],"accuracy":[174],"performace":[175],"aplications,":[179],"substantial":[181],"recognition":[182],"improvement":[183],"over":[184],"baseline.":[186]},"counts_by_year":[{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
