{"id":"https://openalex.org/W7127298350","doi":"https://doi.org/10.1109/jiot.2026.3660732","title":"Pose Recognition System Using Bluetooth Low Energy and Machine Learning Techniques","display_name":"Pose Recognition System Using Bluetooth Low Energy and Machine Learning Techniques","publication_year":2026,"publication_date":"2026-02-03","ids":{"openalex":"https://openalex.org/W7127298350","doi":"https://doi.org/10.1109/jiot.2026.3660732"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2026.3660732","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3660732","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/jiot.2026.3660732","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065530599","display_name":"Igor Vinicius Pereira","orcid":null},"institutions":[{"id":"https://openalex.org/I1283613182","display_name":"Universidade Tecnol\u00f3gica Federal do Paran\u00e1","ror":"https://ror.org/002v2kq79","country_code":"BR","type":"education","lineage":["https://openalex.org/I1283613182"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Igor Vin\u00edcius Pereira","raw_affiliation_strings":["Graduate Program in Energy Systems (PPGSE-CT), Federal University of Technology&#x2014;Paran&#x00E1; (UTFPR), Curitiba, Paran\u00c3\u00a1, Brazil"],"raw_orcid":"https://orcid.org/0009-0002-8974-098X","affiliations":[{"raw_affiliation_string":"Graduate Program in Energy Systems (PPGSE-CT), Federal University of Technology&#x2014;Paran&#x00E1; (UTFPR), Curitiba, Paran\u00c3\u00a1, Brazil","institution_ids":["https://openalex.org/I1283613182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123040197","display_name":"Guilherme De Santi Peron","orcid":null},"institutions":[{"id":"https://openalex.org/I1283613182","display_name":"Universidade Tecnol\u00f3gica Federal do Paran\u00e1","ror":"https://ror.org/002v2kq79","country_code":"BR","type":"education","lineage":["https://openalex.org/I1283613182"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Guilherme de Santi Peron","raw_affiliation_strings":["Graduate Program in Energy Systems (PPGSE-CT), Federal University of Technology&#x2014;Paran&#x00E1; (UTFPR), Curitiba, Paran\u00c3\u00a1, Brazil"],"raw_orcid":"https://orcid.org/0000-0001-5794-0237","affiliations":[{"raw_affiliation_string":"Graduate Program in Energy Systems (PPGSE-CT), Federal University of Technology&#x2014;Paran&#x00E1; (UTFPR), Curitiba, Paran\u00c3\u00a1, Brazil","institution_ids":["https://openalex.org/I1283613182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056965604","display_name":"Marcos Eduardo Pivaro Monteiro","orcid":"https://orcid.org/0000-0001-7658-2025"},"institutions":[{"id":"https://openalex.org/I1283613182","display_name":"Universidade Tecnol\u00f3gica Federal do Paran\u00e1","ror":"https://ror.org/002v2kq79","country_code":"BR","type":"education","lineage":["https://openalex.org/I1283613182"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Marcos Eduardo Pivaro Monteiro","raw_affiliation_strings":["Graduate Program in Electrical and Computer Engineering (CPGEI-CT), Federal University of Technology&#x2014;Paran&#x00E1; (UTFPR), Curitiba, Paran\u00c3\u00a1, Brazil"],"raw_orcid":"https://orcid.org/0000-0001-7658-2025","affiliations":[{"raw_affiliation_string":"Graduate Program in Electrical and Computer Engineering (CPGEI-CT), Federal University of Technology&#x2014;Paran&#x00E1; (UTFPR), Curitiba, Paran\u00c3\u00a1, Brazil","institution_ids":["https://openalex.org/I1283613182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123791363","display_name":"Glauber Brante","orcid":null},"institutions":[{"id":"https://openalex.org/I1283613182","display_name":"Universidade Tecnol\u00f3gica Federal do Paran\u00e1","ror":"https://ror.org/002v2kq79","country_code":"BR","type":"education","lineage":["https://openalex.org/I1283613182"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Glauber Brante","raw_affiliation_strings":["Graduate Program in Electrical and Computer Engineering (CPGEI-CT), Federal University of Technology&#x2014;Paran&#x00E1; (UTFPR), Curitiba, Paran\u00c3\u00a1, Brazil"],"raw_orcid":"https://orcid.org/0000-0001-6006-4274","affiliations":[{"raw_affiliation_string":"Graduate Program in Electrical and Computer Engineering (CPGEI-CT), Federal University of Technology&#x2014;Paran&#x00E1; (UTFPR), Curitiba, Paran\u00c3\u00a1, Brazil","institution_ids":["https://openalex.org/I1283613182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004228037","display_name":"Ohara Kerusauskas Rayel","orcid":"https://orcid.org/0000-0002-9543-9811"},"institutions":[{"id":"https://openalex.org/I1283613182","display_name":"Universidade Tecnol\u00f3gica Federal do Paran\u00e1","ror":"https://ror.org/002v2kq79","country_code":"BR","type":"education","lineage":["https://openalex.org/I1283613182"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Ohara Kerusauskas Rayel","raw_affiliation_strings":["Graduate Program in Energy Systems (PPGSE-CT), Federal University of Technology&#x2014;Paran&#x00E1; (UTFPR), Curitiba, Paran\u00c3\u00a1, Brazil"],"raw_orcid":"https://orcid.org/0000-0002-9543-9811","affiliations":[{"raw_affiliation_string":"Graduate Program in Energy Systems (PPGSE-CT), Federal University of Technology&#x2014;Paran&#x00E1; (UTFPR), Curitiba, Paran\u00c3\u00a1, Brazil","institution_ids":["https://openalex.org/I1283613182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083324363","display_name":"Guilherme Luiz Moritz","orcid":"https://orcid.org/0000-0003-3628-2321"},"institutions":[{"id":"https://openalex.org/I1283613182","display_name":"Universidade Tecnol\u00f3gica Federal do Paran\u00e1","ror":"https://ror.org/002v2kq79","country_code":"BR","type":"education","lineage":["https://openalex.org/I1283613182"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Guilherme Luiz Moritz","raw_affiliation_strings":["Graduate Program in Energy Systems (PPGSE-CT), Federal University of Technology&#x2014;Paran&#x00E1; (UTFPR), Curitiba, Paran\u00c3\u00a1, Brazil"],"raw_orcid":"https://orcid.org/0000-0003-3628-2321","affiliations":[{"raw_affiliation_string":"Graduate Program in Energy Systems (PPGSE-CT), Federal University of Technology&#x2014;Paran&#x00E1; (UTFPR), Curitiba, Paran\u00c3\u00a1, Brazil","institution_ids":["https://openalex.org/I1283613182"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124124767","display_name":"Richard Demo Souza","orcid":null},"institutions":[{"id":"https://openalex.org/I4104125","display_name":"Universidade Federal de Santa Catarina","ror":"https://ror.org/041akq887","country_code":"BR","type":"education","lineage":["https://openalex.org/I4104125"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Richard Demo Souza","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Federal University of Santa Catarina (UFSC), Florian&#x00F3;polis, Santa Catarina, Brazil"],"raw_orcid":"https://orcid.org/0000-0002-7389-6245","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Federal University of Santa Catarina (UFSC), Florian&#x00F3;polis, Santa Catarina, Brazil","institution_ids":["https://openalex.org/I4104125"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12156506,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"8","first_page":"16815","last_page":"16830"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.5927000045776367,"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":0.5927000045776367,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.08739999681711197,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12740","display_name":"Gait Recognition and Analysis","score":0.045899998396635056,"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/bluetooth-low-energy","display_name":"Bluetooth Low Energy","score":0.7475000023841858},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6000000238418579},{"id":"https://openalex.org/keywords/bluetooth","display_name":"Bluetooth","score":0.5953999757766724},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5812000036239624},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.5619000196456909},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.5051000118255615},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4927999973297119},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44929999113082886},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4345000088214874}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8349999785423279},{"id":"https://openalex.org/C2776418194","wikidata":"https://www.wikidata.org/wiki/Q1638779","display_name":"Bluetooth Low Energy","level":4,"score":0.7475000023841858},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.694100022315979},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6000000238418579},{"id":"https://openalex.org/C546215728","wikidata":"https://www.wikidata.org/wiki/Q39531","display_name":"Bluetooth","level":3,"score":0.5953999757766724},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5812000036239624},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.5619000196456909},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.5051000118255615},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4927999973297119},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4675999879837036},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44929999113082886},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4345000088214874},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42309999465942383},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41749998927116394},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39489999413490295},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3917999863624573},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.36419999599456787},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.3521000146865845},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3416999876499176},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.32100000977516174},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3142000138759613},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.3116999864578247},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3077000081539154},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.305400013923645},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C2989164559","wikidata":"https://www.wikidata.org/wiki/Q15637420","display_name":"Low energy","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C75172450","wikidata":"https://www.wikidata.org/wiki/Q623950","display_name":"Fast Fourier transform","level":2,"score":0.25130000710487366},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.25049999356269836},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2026.3660732","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3660732","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/jiot.2026.3660732","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3660732","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2347713866","display_name":null,"funder_award_id":"306359/2025-1","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"},{"id":"https://openalex.org/G2760762640","display_name":null,"funder_award_id":"307226/2021-2","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"},{"id":"https://openalex.org/G5764978312","display_name":null,"funder_award_id":"01245.020548/2021-07","funder_id":"https://openalex.org/F4320317482","funder_display_name":"Rede Nacional de Ensino e Pesquisa"},{"id":"https://openalex.org/G5767851649","display_name":null,"funder_award_id":"PD05697-1323/2023","funder_id":"https://openalex.org/F4320324178","funder_display_name":"Ag\u00eancia Nacional de Energia El\u00e9trica"},{"id":"https://openalex.org/G8104560750","display_name":null,"funder_award_id":"305021/2021-4","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"}],"funders":[{"id":"https://openalex.org/F4320317482","display_name":"Rede Nacional de Ensino e Pesquisa","ror":"https://ror.org/04hztxs45"},{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"},{"id":"https://openalex.org/F4320324178","display_name":"Ag\u00eancia Nacional de Energia El\u00e9trica","ror":"https://ror.org/049sgh675"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"study":[1,264],"addresses":[2],"the":[3,109,143,175,180,186,207,229,254],"challenge":[4],"of":[5,27,108,151,162],"robust":[6,237],"human":[7],"pose":[8],"recognition":[9],"in":[10,71,124],"complex":[11],"indoor":[12,74],"environments":[13],"by":[14,142,185,206,228],"proposing":[15],"a":[16,44,72,88,96,158,267],"system":[17],"that":[18,247],"generalizes":[19],"to":[20,253,271],"unseen":[21],"user":[22],"locations":[23],"using":[24,76,248],"only":[25],"Angle":[26],"Arrival":[28],"(AoA)":[29],"data":[30],"from":[31],"Bluetooth":[32],"Low":[33],"Energy":[34],"(BLE)":[35],"5.1":[36],"devices.":[37],"A":[38],"comparative":[39],"evaluation":[40],"was":[41,140,183],"performed,":[42],"assessing":[43],"Random":[45],"Forest":[46],"model":[47],"alongside":[48],"three":[49],"neural":[50],"network":[51],"architectures\u2014":[52],"CNN,":[53],"LSTM,":[54],"and":[55,66,91,95,106,126,157,197,218,257,274],"hybrid":[56],"models\u2014for":[57],"identifying":[58],"four":[59,249],"physical":[60],"states:":[61],"standing,":[62],"sitting,":[63],"lying":[64],"down,":[65],"walking.":[67],"Data":[68],"were":[69,115],"collected":[70],"real":[73],"environment":[75],"smart":[77],"Personal":[78],"Protective":[79],"Equipment":[80],"(PPE)":[81],"equipped":[82],"with":[83,177,191,212],"BLE":[84],"transmitters":[85],"placed":[86],"on":[87,137],"helmet,":[89],"upper":[90],"lower":[92],"shirt":[93],"regions,":[94],"boot.":[97],"The":[98,133,244,263],"preprocessing":[99],"pipeline":[100],"included":[101],"filtering,":[102],"interpolation,":[103],"feature":[104],"extraction,":[105],"application":[107],"Fast":[110],"Fourier":[111],"Transform":[112],"(FFT).":[113],"Models":[114],"evaluated":[116],"under":[117],"two":[118],"scenarios:":[119],"(i)":[120],"known":[121,178],"positions":[122,129,139],"(used":[123],"training)":[125],"(ii)":[127],"unknown":[128,138],"(never":[130],"seen":[131],"before).":[132],"best":[134],"overall":[135],"performance":[136,182],"achieved":[141],"<italic":[144,152,163,187,192,198,208,213,219,230],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[145,153,164,166,188,193,199,201,209,214,220,222,231],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Attention-based":[146,232],"BiLSTM\u2013CNN,</i>":[147,233],"reaching":[148],"an":[149],"accuracy":[150,239],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">A</i>":[154,194,215],"=":[155,168,195,203,216,224],"94.89%":[156],"macro":[159],"averaged":[160],"F1-score":[161],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">F</i><sub":[165,200,221],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[167,202,223],"95.59%,":[169],"demonstrating":[170],"strong":[171],"generalization":[172],"capabilities.":[173],"In":[174],"scenario":[176],"positions,":[179],"highest":[181,255],"obtained":[184],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Random":[189],"Forest</i>,":[190],"99.95%":[196],"99.95%,":[204],"followed":[205,227],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Deep":[210],"CNN,</i>":[211],"97.27%":[217],"97.28%,":[225],"closely":[226],"which":[234],"also":[235,265],"showed":[236],"classification":[238],"across":[240],"all":[241],"posture":[242],"classes.":[243],"analysis":[245],"confirmed":[246],"wearable":[250],"devices":[251],"led":[252],"performance,":[256],"sensor":[258],"combinations":[259],"significantly":[260],"affected":[261],"accuracy.":[262],"provides":[266],"publicly":[268],"available":[269],"dataset":[270],"support":[272],"reproducibility":[273],"benchmarking.":[275]},"counts_by_year":[],"updated_date":"2026-06-24T13:16:06.693445","created_date":"2026-02-04T00:00:00"}