{"id":"https://openalex.org/W2887499899","doi":"https://doi.org/10.1109/memea.2018.8438750","title":"Human Activity Recognition by Wearable Sensors : Comparison of different classifiers for real-time applications","display_name":"Human Activity Recognition by Wearable Sensors : Comparison of different classifiers for real-time applications","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2887499899","doi":"https://doi.org/10.1109/memea.2018.8438750","mag":"2887499899"},"language":"en","primary_location":{"id":"doi:10.1109/memea.2018.8438750","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea.2018.8438750","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","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/A5084589848","display_name":"G Leonardis","orcid":null},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"G. De Leonardis","raw_affiliation_strings":["Politecnico di Torino, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012791314","display_name":"Samanta Rosati","orcid":"https://orcid.org/0000-0003-0620-594X"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"S. Rosati","raw_affiliation_strings":["Politecnico di Torino, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011367557","display_name":"Gabriella Balestra","orcid":"https://orcid.org/0000-0003-2717-648X"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"G. Balestra","raw_affiliation_strings":["Politecnico di Torino, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074775900","display_name":"Valentina Agostini","orcid":"https://orcid.org/0000-0001-5887-1499"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"V. Agostini","raw_affiliation_strings":["Politecnico di Torino, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002558004","display_name":"Elisa Panero","orcid":"https://orcid.org/0000-0002-5555-5818"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"E. Panero","raw_affiliation_strings":["Politecnico di Torino, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068373340","display_name":"Laura Gastaldi","orcid":"https://orcid.org/0000-0002-0572-1240"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"L. Gastaldi","raw_affiliation_strings":["Politecnico di Torino, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078474054","display_name":"Marco Knaflitz","orcid":"https://orcid.org/0000-0001-5396-5103"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"M. Knaflitz","raw_affiliation_strings":["Politecnico di Torino, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5084589848"],"corresponding_institution_ids":["https://openalex.org/I177477856"],"apc_list":null,"apc_paid":null,"fwci":4.3297,"has_fulltext":false,"cited_by_count":90,"citation_normalized_percentile":{"value":0.95993929,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9997000098228455,"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":0.9997000098228455,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9943000078201294,"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/T13248","display_name":"Healthcare Technology and Patient Monitoring","score":0.9559000134468079,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/computer-science","display_name":"Computer science","score":0.7441697120666504},{"id":"https://openalex.org/keywords/gyroscope","display_name":"Gyroscope","score":0.737932562828064},{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.7183395624160767},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7055742740631104},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6730536222457886},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.6086826324462891},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5904561281204224},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5734250545501709},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.5197077393531799},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5134104490280151},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5061108469963074},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44428786635398865},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.43008118867874146},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4242519438266754},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4152088761329651},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.36801546812057495},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1528390347957611},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.09475132822990417}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7441697120666504},{"id":"https://openalex.org/C158488048","wikidata":"https://www.wikidata.org/wiki/Q483400","display_name":"Gyroscope","level":2,"score":0.737932562828064},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.7183395624160767},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7055742740631104},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6730536222457886},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.6086826324462891},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5904561281204224},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5734250545501709},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.5197077393531799},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5134104490280151},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5061108469963074},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44428786635398865},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.43008118867874146},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4242519438266754},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4152088761329651},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.36801546812057495},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1528390347957611},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.09475132822990417},{"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/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/memea.2018.8438750","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea.2018.8438750","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1495617916","https://openalex.org/W1526455201","https://openalex.org/W1993761347","https://openalex.org/W1995341919","https://openalex.org/W2003948557","https://openalex.org/W2413484788","https://openalex.org/W2491430782","https://openalex.org/W2507653100","https://openalex.org/W2547300370","https://openalex.org/W2562935526","https://openalex.org/W2593796416","https://openalex.org/W2610534732","https://openalex.org/W2620668779","https://openalex.org/W2749649762","https://openalex.org/W2759690896","https://openalex.org/W2763567083","https://openalex.org/W2766046425","https://openalex.org/W2770265759","https://openalex.org/W2773643445","https://openalex.org/W2774090517","https://openalex.org/W2781777756","https://openalex.org/W2785835609","https://openalex.org/W2795739367","https://openalex.org/W2798741797","https://openalex.org/W3145506661","https://openalex.org/W4206070770","https://openalex.org/W4292890447","https://openalex.org/W6742787260","https://openalex.org/W6747090629","https://openalex.org/W6748151310"],"related_works":["https://openalex.org/W2356006086","https://openalex.org/W2545168295","https://openalex.org/W4234814094","https://openalex.org/W1973973903","https://openalex.org/W2365897603","https://openalex.org/W2156308897","https://openalex.org/W3195533899","https://openalex.org/W3208523813","https://openalex.org/W4287084017","https://openalex.org/W3179745820"],"abstract_inverted_index":{"In":[0,49,239],"recent":[1],"years,":[2],"there":[3,61],"is":[4,20,76],"a":[5,24,29,41,63,98,232,258],"growing":[6],"interest":[7],"in":[8,15,134,142],"Human":[9],"Activity":[10],"Recognition":[11],"(HAR)":[12],"systems":[13],"applied":[14],"healthcare.":[16],"A":[17],"HAR":[18,102],"system":[19],"essentially":[21],"made":[22],"of":[23,31,57,73,81,94,150,163,210,223,231,261],"wearable":[25,99],"device":[26],"equipped":[27],"with":[28],"set":[30],"sensors":[32],"(like":[33],"accelerometers,":[34],"gyroscopes,":[35],"magnetometers,":[36],"heart-rate":[37],"sensors,":[38],"etc...)":[39],"and":[40,65,92,100,107,128,136,145,156,192,221,251,254],"classifier":[42,225,242],"able":[43,203],"to":[44,77,138,165,204],"recognize":[45,206],"the":[46,55,58,74,79,161,174,234,262],"activity":[47],"performed.":[48],"this":[50,241],"study":[51,75],"we":[52,89,120,159],"focused":[53],"on":[54,85],"choice":[56],"classifier,":[59],"since":[60],"isn't":[62],"unique":[64],"consolidated":[66],"methodology":[67],"for":[68,173,226,257],"HAR.":[69],"The":[70,212],"main":[71],"aim":[72],"compare":[78],"performances":[80,214],"5":[82,176],"classifiers,":[83],"based":[84],"machine":[86],"learning.":[87],"Furthermore,":[88],"analyzed":[90],"advantages":[91,220],"disadvantages":[93,222],"their":[95],"implementation":[96,228],"onto":[97],"realtime":[101],"system.":[103],"We":[104],"acquired":[105],"magnetic":[106],"inertial":[108],"measurement":[109],"unit":[110],"(MIMU)":[111],"signals":[112,123,131],"from":[113,124],"15":[114],"young":[115],"volunteers.":[116],"For":[117],"each":[118,224],"subject,":[119],"recorded":[121],"9":[122],"tri-axis":[125],"accelerometer,":[126],"gyroscope":[127],"magnetometer.":[129],"All":[130],"were":[132,169,202,215],"divided":[133],"5s-windows":[135],"processed":[137],"extract":[139],"342":[140],"features":[141,164,168],"time,":[143],"frequency":[144],"time-frequency":[146],"domains.":[147],"By":[148],"means":[149,230],"two":[151],"feature":[152],"selection":[153],"steps":[154],"(correlation-based":[155],"genetic":[157],"algorithm),":[158],"reduced":[160],"number":[162],"69.":[166],"These":[167],"used":[170],"as":[171],"input":[172],"following":[175],"classifiers:":[177],"K-Nearest":[178],"Neighbor":[179],"(KNN),":[180],"Feedforward":[181],"Neural":[182],"Network":[183],"(FNN),":[184],"Support":[185],"Vector":[186],"Machines":[187],"(SVM),":[188],"Na\u00efve":[189],"Bayes":[190],"(NB),":[191],"Decision":[193],"Tree":[194],"(DT).":[195],"Our":[196],"results":[197],"showed":[198],"that":[199],"all":[200],"classifiers":[201],"correctly":[205],"more":[207],"than":[208],"90%":[209],"activities.":[211],"best":[213],"obtained":[216],"by":[217,229],"KNN.":[218],"Analyzing":[219],"its":[227],"microcontroller":[233],"most":[235],"suitable":[236],"was":[237],"DT.":[238],"fact,":[240],"can":[243],"be":[244],"easily":[245],"implemented,":[246],"it":[247,255],"has":[248],"low":[249],"memory":[250],"computational":[252],"requirements,":[253],"allows":[256],"further":[259],"reduction":[260],"required":[263],"features.":[264]},"counts_by_year":[{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":17},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":1}],"updated_date":"2026-03-05T09:29:38.588285","created_date":"2025-10-10T00:00:00"}