{"id":"https://openalex.org/W3114040862","doi":"https://doi.org/10.1145/3432701","title":"MM-Fit","display_name":"MM-Fit","publication_year":2020,"publication_date":"2020-12-17","ids":{"openalex":"https://openalex.org/W3114040862","doi":"https://doi.org/10.1145/3432701","mag":"3114040862"},"language":"en","primary_location":{"id":"doi:10.1145/3432701","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3432701","pdf_url":null,"source":{"id":"https://openalex.org/S4210219751","display_name":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","issn_l":"2474-9567","issn":["2474-9567"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies","raw_type":"journal-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/A5076304642","display_name":"David Str\u00f6mb\u00e4ck","orcid":null},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"David Str\u00f6mb\u00e4ck","raw_affiliation_strings":["University of Edinburgh, Edinburgh, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047872044","display_name":"Sangxia Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210129561","display_name":"Sony (Sweden)","ror":"https://ror.org/02t8vgv97","country_code":"SE","type":"company","lineage":["https://openalex.org/I4210129561","https://openalex.org/I4210143797"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Sangxia Huang","raw_affiliation_strings":["R&D Center Lund Laboratory, Sony Europe, Lund, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"R&D Center Lund Laboratory, Sony Europe, Lund, Sweden","institution_ids":["https://openalex.org/I4210129561"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007676144","display_name":"Valentin Radu","orcid":"https://orcid.org/0000-0003-3502-4355"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]},{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Valentin Radu","raw_affiliation_strings":["University of Edinburgh, University of Sheffield, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Edinburgh, University of Sheffield, UK","institution_ids":["https://openalex.org/I98677209","https://openalex.org/I91136226"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076304642"],"corresponding_institution_ids":["https://openalex.org/I98677209"],"apc_list":null,"apc_paid":null,"fwci":2.9426,"has_fulltext":false,"cited_by_count":63,"citation_normalized_percentile":{"value":0.92792211,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"4","issue":"4","first_page":"1","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9994999766349792,"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":0.9994999766349792,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9987999796867371,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9793000221252441,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7645249366760254},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6923919916152954},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.6649090647697449},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.6494134068489075},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6029041409492493},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.594193696975708},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.588383138179779},{"id":"https://openalex.org/keywords/smartwatch","display_name":"Smartwatch","score":0.5488144755363464},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.5326356887817383},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5215470790863037},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.5035361647605896},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4583629071712494},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4487190246582031},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.4443921744823456},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.4368702471256256},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3735905885696411},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34044793248176575}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7645249366760254},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6923919916152954},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.6649090647697449},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.6494134068489075},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6029041409492493},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.594193696975708},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.588383138179779},{"id":"https://openalex.org/C29794715","wikidata":"https://www.wikidata.org/wiki/Q5362345","display_name":"Smartwatch","level":3,"score":0.5488144755363464},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.5326356887817383},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5215470790863037},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.5035361647605896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4583629071712494},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4487190246582031},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.4443921744823456},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.4368702471256256},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3735905885696411},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34044793248176575},{"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3432701","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3432701","pdf_url":null,"source":{"id":"https://openalex.org/S4210219751","display_name":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","issn_l":"2474-9567","issn":["2474-9567"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W605243474","https://openalex.org/W1534268656","https://openalex.org/W1950788856","https://openalex.org/W1991239827","https://openalex.org/W2002261403","https://openalex.org/W2010590614","https://openalex.org/W2021150171","https://openalex.org/W2023302299","https://openalex.org/W2037265949","https://openalex.org/W2048821851","https://openalex.org/W2054780155","https://openalex.org/W2056339039","https://openalex.org/W2057907879","https://openalex.org/W2059732136","https://openalex.org/W2059983432","https://openalex.org/W2094558311","https://openalex.org/W2101032778","https://openalex.org/W2106996050","https://openalex.org/W2109606373","https://openalex.org/W2110819057","https://openalex.org/W2112796928","https://openalex.org/W2118931255","https://openalex.org/W2140944144","https://openalex.org/W2156387975","https://openalex.org/W2184188583","https://openalex.org/W2200707618","https://openalex.org/W2243012843","https://openalex.org/W2344284192","https://openalex.org/W2415469094","https://openalex.org/W2519804223","https://openalex.org/W2559085405","https://openalex.org/W2593390416","https://openalex.org/W2604321021","https://openalex.org/W2605740512","https://openalex.org/W2612706635","https://openalex.org/W2736191430","https://openalex.org/W2775529075","https://openalex.org/W2777460464","https://openalex.org/W2784435047","https://openalex.org/W2869166307","https://openalex.org/W2890264806","https://openalex.org/W2907057563","https://openalex.org/W2907706589","https://openalex.org/W2914426823","https://openalex.org/W2940457086","https://openalex.org/W2963073306","https://openalex.org/W2963076818","https://openalex.org/W2963218601","https://openalex.org/W2964121744","https://openalex.org/W2964350365","https://openalex.org/W3011489775","https://openalex.org/W3034851746","https://openalex.org/W3098538019","https://openalex.org/W3103858256","https://openalex.org/W4300870429","https://openalex.org/W4301045096","https://openalex.org/W4392251558"],"related_works":["https://openalex.org/W2748818549","https://openalex.org/W4304142278","https://openalex.org/W3032336428","https://openalex.org/W2342865424","https://openalex.org/W2587509230","https://openalex.org/W4283331601","https://openalex.org/W3097068272","https://openalex.org/W4210780304","https://openalex.org/W2802035586","https://openalex.org/W3093846146"],"abstract_inverted_index":{"Fitness":[0],"tracking":[1,30],"devices":[2,146],"have":[3],"risen":[4],"in":[5,7,12,176],"popularity":[6],"recent":[8],"years,":[9],"but":[10],"limitations":[11],"terms":[13],"of":[14,66,112,133,144,154],"their":[15],"accuracy":[16,168],"and":[17,47,53,73,82,89,101,108,125,135,147,192,220,238,241],"failure":[18],"to":[19,40,235],"track":[20],"many":[21],"common":[22],"exercises":[23],"presents":[24],"a":[25,35,63,95,142,222],"need":[26],"for":[27,45,98,138,162,244],"improved":[28],"fitness":[29],"solutions.":[31],"This":[32],"work":[33],"proposes":[34],"multimodal":[36,136,155],"deep":[37,156],"learning":[38,157,159],"approach":[39],"leverage":[41],"multiple":[42],"data":[43,69,182,195],"sources":[44],"robust":[46],"accurate":[48],"activity":[49,99,139,163],"segmentation,":[50],"exercise":[51,102,240,246],"recognition":[52,103,140],"repetition":[54,224],"counting.":[55],"For":[56],"this,":[57],"we":[58,150,218],"introduce":[59],"the":[60,105,110,131,152,177,184,189,197,206,213],"MM-Fit":[61,106,178,229],"dataset;":[62,179],"substantial":[64],"collection":[65],"inertial":[67,123],"sensor":[68,124],"from":[70,122,183,188,196],"smartphones,":[71],"smartwatches":[72],"earbuds":[74],"worn":[75],"by":[76,204],"participants":[77],"while":[78],"performing":[79],"full-body":[80],"workouts,":[81],"time-synchronised":[83],"multi-viewpoint":[84],"RGB-D":[85],"video,":[86],"with":[87],"2D":[88],"3D":[90],"pose":[91],"estimates.":[92],"We":[93,129,200],"establish":[94],"strong":[96,223],"baseline":[97,226],"segmentation":[100],"on":[104,173,194,227],"dataset,":[107],"demonstrate":[109,151],"effectiveness":[111,153],"our":[113,228],"CNN-based":[114],"architecture":[115],"at":[116,158],"extracting":[117],"modality-specific":[118],"spatial":[119],"temporal":[120],"features":[121],"skeleton":[126],"sequence":[127],"data.":[128],"compare":[130],"performance":[132,203],"unimodal":[134],"models":[137],"across":[141,169],"number":[143],"sensing":[145,171,215],"modalities.":[148,216],"Furthermore,":[149],"cross-modal":[160],"representations":[161],"recognition,":[164],"which":[165,210],"achieves":[166],"96%":[167],"all":[170],"modalities":[172],"unseen":[174],"subjects":[175],"94%":[180],"using":[181,205],"smartwatch":[185],"only;":[186,191],"85%":[187],"smartphone":[190],"82%":[193],"earbud":[198],"device.":[199],"strengthen":[201],"single-device":[202],"zeroing-out":[207],"training":[208],"strategy,":[209],"phases":[211],"out":[212],"other":[214],"Finally,":[217],"implement":[219],"evaluate":[221],"counting":[225],"dataset.":[230],"Collectively,":[231],"these":[232],"tasks":[233],"contribute":[234],"recognising,":[236],"segmenting":[237],"timing":[239],"non-exercise":[242],"activities":[243],"automatic":[245],"logging.":[247]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":4}],"updated_date":"2026-06-05T09:01:59.212387","created_date":"2021-01-05T00:00:00"}