{"id":"https://openalex.org/W4409310761","doi":"https://doi.org/10.1109/access.2025.3559182","title":"Enhanced Detection of Hand Gestures From sEMG Signals Using Stacking Ensemble With Particle Swarm Optimization and Meta-Classifier","display_name":"Enhanced Detection of Hand Gestures From sEMG Signals Using Stacking Ensemble With Particle Swarm Optimization and Meta-Classifier","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4409310761","doi":"https://doi.org/10.1109/access.2025.3559182"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3559182","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3559182","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3559182","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5117093552","display_name":"Umesh Chandra Sakinala","orcid":null},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Umesh Chandra Sakinala","raw_affiliation_strings":["School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India"],"raw_orcid":"https://orcid.org/0009-0006-2318-5505","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054930513","display_name":"S. Abinaya","orcid":"https://orcid.org/0000-0001-7957-7934"},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"S. Abinaya","raw_affiliation_strings":["School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India"],"raw_orcid":"https://orcid.org/0000-0001-7957-7934","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India","institution_ids":["https://openalex.org/I876193797"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I876193797"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.4223,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57079652,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"13","issue":null,"first_page":"63611","last_page":"63626"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9876000285148621,"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"}},"topics":[{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9876000285148621,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.987500011920929,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9814000129699707,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.7781840562820435},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7335827350616455},{"id":"https://openalex.org/keywords/stacking","display_name":"Stacking","score":0.6998014450073242},{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.6783131957054138},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.605918824672699},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5995293259620667},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5749355554580688},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.43152523040771484},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4276214838027954},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2704557776451111},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08504071831703186},{"id":"https://openalex.org/keywords/nuclear-magnetic-resonance","display_name":"Nuclear magnetic resonance","score":0.06762972474098206}],"concepts":[{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.7781840562820435},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7335827350616455},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.6998014450073242},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.6783131957054138},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.605918824672699},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5995293259620667},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5749355554580688},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.43152523040771484},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4276214838027954},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2704557776451111},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08504071831703186},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.06762972474098206}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3559182","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3559182","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:bf5040ee121a488c9efe71e2bc38a22c","is_oa":true,"landing_page_url":"https://doaj.org/article/bf5040ee121a488c9efe71e2bc38a22c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 63611-63626 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3559182","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3559182","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2119008936","https://openalex.org/W2123167643","https://openalex.org/W2170613067","https://openalex.org/W2516710120","https://openalex.org/W2800930771","https://openalex.org/W2807631444","https://openalex.org/W2898980383","https://openalex.org/W2912302853","https://openalex.org/W2962879438","https://openalex.org/W2981991692","https://openalex.org/W2984329907","https://openalex.org/W2997516327","https://openalex.org/W3039224603","https://openalex.org/W3043248516","https://openalex.org/W3099685148","https://openalex.org/W3163487808","https://openalex.org/W4226380415","https://openalex.org/W4280514173","https://openalex.org/W4297347800","https://openalex.org/W4323319976","https://openalex.org/W4380904824","https://openalex.org/W4388517737","https://openalex.org/W4390576512","https://openalex.org/W4393171264","https://openalex.org/W6801523839"],"related_works":["https://openalex.org/W2035329725","https://openalex.org/W2070875936","https://openalex.org/W2902873204","https://openalex.org/W2185750513","https://openalex.org/W2010878661","https://openalex.org/W3147379364","https://openalex.org/W2026258298","https://openalex.org/W3204639664","https://openalex.org/W2970836791","https://openalex.org/W2989699735"],"abstract_inverted_index":{"Hand":[0],"gesture":[1,195],"recognition":[2,14,196],"is":[3,27,103,155],"a":[4,28,98,106,110,142,169],"key":[5],"aspect":[6],"of":[7,15,172,179,186,194],"Human":[8],"Computer":[9],"Interaction":[10],"(HCI),":[11],"that":[12,114],"enables":[13],"hand":[16],"movements":[17],"or":[18],"gestures":[19,164],"through":[20,121],"sensors":[21],"and":[22,67,78,86,117,168,181],"cameras.":[23],"Surface":[24],"Electromyography":[25],"(sEMG)":[26],"technique":[29,145],"used":[30],"to":[31,73,90,125,134],"measure":[32],"electrical":[33],"signals":[34,42,61,66],"generated":[35],"by":[36,46],"human":[37],"muscle":[38,52],"activity.":[39],"Analyzing":[40],"sEMG":[41,60,92],"are":[43],"highly":[44],"influenced":[45],"the":[47,84,127,136,139,158,184,192],"factors":[48,74],"like":[49],"electrode":[50],"placement,":[51],"contraction":[53],"patterns":[54,189],"etc.":[55],"Existing":[56],"methodologies":[57],"for":[58,129,151,190],"detecting":[59],"face":[62],"challenges":[63],"in":[64],"interpreting":[65],"frequency":[68],"feature":[69],"variations,":[70],"primarily":[71],"due":[72],"such":[75],"as":[76],"noise":[77],"motion":[79],"artifacts,":[80],"which":[81,146],"significantly":[82],"limit":[83],"accuracy":[85,178],"reliability":[87],"when":[88],"applied":[89],"large":[91],"datasets.":[93],"To":[94],"overcome":[95],"these":[96],"challenges,":[97],"cutting-edge":[99],"deep":[100],"learning":[101],"framework":[102],"proposed,":[104],"combining":[105],"convolutional":[107],"autoencoder":[108],"with":[109,162],"stacking":[111],"ensemble":[112],"method":[113],"integrates":[115],"CNN":[116],"LSTM":[118],"models,":[119],"optimized":[120],"particle":[122],"swarm":[123],"optimization":[124],"fine-tune":[126],"hyperparameters":[128],"superior":[130],"training":[131],"performance.":[132],"Further":[133],"reduce":[135],"prediction":[137],"error,":[138],"model":[140],"employs":[141],"Meta":[143],"classifier":[144],"incorporates":[147],"Random":[148],"Forests":[149],"approach":[150],"improved":[152],"accuracy.":[153],"It":[154,175],"evaluated":[156],"on":[157],"NinaPro":[159],"DB1":[160],"dataset":[161],"27":[163],"from":[165],"52":[166],"subjects":[167],"window":[170],"length":[171],"500":[173],"ms.":[174],"achieves":[176],"high":[177],"85%":[180],"effectively":[182],"mitigates":[183],"impact":[185],"erroneous":[187],"data":[188],"advancing":[191],"robustness":[193],"systems.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
