{"id":"https://openalex.org/W4416749512","doi":"https://doi.org/10.1109/iros60139.2025.11247465","title":"Cross-Activity sEMG-Driven Joint Angle Estimation via Hybrid Attention Fusion: Bridging Traditional Features and Deep Spatial Representations","display_name":"Cross-Activity sEMG-Driven Joint Angle Estimation via Hybrid Attention Fusion: Bridging Traditional Features and Deep Spatial Representations","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416749512","doi":"https://doi.org/10.1109/iros60139.2025.11247465"},"language":null,"primary_location":{"id":"doi:10.1109/iros60139.2025.11247465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11247465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5101905596","display_name":"Zhimin Tang","orcid":"https://orcid.org/0000-0002-9265-5578"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhimin Tang","raw_affiliation_strings":["South China University of Technology,School of Automation Science and Engineering,Guangzhou,China,510641"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology,School of Automation Science and Engineering,Guangzhou,China,510641","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100512558","display_name":"Xiaoyan Deng","orcid":"https://orcid.org/0000-0002-5391-766X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyan Deng","raw_affiliation_strings":["South China University of Technology,School of Automation Science and Engineering,Guangzhou,China,510641"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology,School of Automation Science and Engineering,Guangzhou,China,510641","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102555171","display_name":"Yinke Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinke Wen","raw_affiliation_strings":["South China University of Technology,School of Automation Science and Engineering,Guangzhou,China,510641"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology,School of Automation Science and Engineering,Guangzhou,China,510641","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103577152","display_name":"Han Xi","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Han","raw_affiliation_strings":["South China University of Technology,School of Automation Science and Engineering,Guangzhou,China,510641"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology,School of Automation Science and Engineering,Guangzhou,China,510641","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109738595","display_name":"Jiatong Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiatong Wu","raw_affiliation_strings":["South China University of Technology,School of Automation Science and Engineering,Guangzhou,China,510641"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology,School of Automation Science and Engineering,Guangzhou,China,510641","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101102417","display_name":"Zhuliang Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuliang Yu","raw_affiliation_strings":["South China University of Technology,School of Automation Science and Engineering,Guangzhou,China,510641"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology,School of Automation Science and Engineering,Guangzhou,China,510641","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29575227,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"14611","last_page":"14616"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.7299000024795532,"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":0.7299000024795532,"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/T11023","display_name":"Prosthetics and Rehabilitation Robotics","score":0.16590000689029694,"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/T10510","display_name":"Stroke Rehabilitation and Recovery","score":0.04839999973773956,"subfield":{"id":"https://openalex.org/subfields/2742","display_name":"Rehabilitation"},"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/robustness","display_name":"Robustness (evolution)","score":0.7045000195503235},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.6140999794006348},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.49720001220703125},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.4860999882221222},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4115000069141388},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.3944000005722046},{"id":"https://openalex.org/keywords/exoskeleton","display_name":"Exoskeleton","score":0.38449999690055847},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3767000138759613},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.364300012588501}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7045000195503235},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6924999952316284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6735000014305115},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.6140999794006348},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.49720001220703125},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.4860999882221222},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44029998779296875},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4115000069141388},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3944000005722046},{"id":"https://openalex.org/C146549078","wikidata":"https://www.wikidata.org/wiki/Q191944","display_name":"Exoskeleton","level":2,"score":0.38449999690055847},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3767000138759613},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.364300012588501},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.34299999475479126},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.3384999930858612},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.33799999952316284},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.334199994802475},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.29440000653266907},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.2784999907016754},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.274399995803833},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.2547999918460846},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros60139.2025.11247465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11247465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320317992","display_name":"Experiment","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2002499457","https://openalex.org/W2077192769","https://openalex.org/W2092623288","https://openalex.org/W2112802476","https://openalex.org/W2276859268","https://openalex.org/W2333544554","https://openalex.org/W2762367260","https://openalex.org/W2805874402","https://openalex.org/W2965100371","https://openalex.org/W2991198759","https://openalex.org/W3012425893","https://openalex.org/W3126426351","https://openalex.org/W3135957997","https://openalex.org/W3136218483","https://openalex.org/W4229061265","https://openalex.org/W4379879449","https://openalex.org/W4387445706","https://openalex.org/W4390874423","https://openalex.org/W4403537025","https://openalex.org/W4404028994"],"related_works":[],"abstract_inverted_index":{"The":[0,55,79,137],"growing":[1],"prevalence":[2],"of":[3,68,95,124],"stroke":[4],"necessitates":[5],"advanced":[6],"lower-limb":[7],"exoskeleton":[8],"control.":[9],"This":[10,165],"paper":[11],"proposes":[12],"HybridFusionAtt,":[13],"a":[14],"novel":[15],"model":[16,56,81,114,138],"for":[17,88],"continuous":[18],"joint":[19,92],"angle":[20,93],"estimation":[21],"using":[22,59],"surface":[23],"electromyography":[24],"(sEMG).":[25],"Unlike":[26],"conventional":[27],"approaches,":[28],"our":[29],"framework":[30],"uniquely":[31],"integrates":[32],"traditional":[33,46,117],"time-domain":[34],"features":[35,40,47,145],"with":[36],"CNN-extracted":[37],"high-dimensional":[38],"spatial":[39],"through":[41],"an":[42],"attention":[43,53],"mechanism,":[44],"where":[45],"dynamically":[48],"guide":[49],"feature":[50],"fusion":[51],"as":[52,134],"queries.":[54],"was":[57],"validated":[58],"data":[60],"collected":[61],"from":[62],"eight":[63],"participants":[64],"performing":[65],"four":[66],"activities":[67],"daily":[69],"living":[70],"(walking,":[71],"stair":[72,74],"climbing,":[73],"descending,":[75],"and":[76,90,104,119,126,146,161,175],"obstacle":[77,135],"crossing).":[78],"proposed":[80,113],"achieves":[82,139],"average":[83],"R<sup":[84],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[85],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[86],"values":[87],"knee":[89],"hip":[91],"prediction":[94],"0.8682":[96],"(walking),":[97],"0.8482":[98],"(obstacle":[99],"crossing),":[100],"0.9294":[101],"(stair":[102,106],"climbing),":[103],"0.8676":[105],"descending).":[107],"Experimental":[108],"results":[109],"show":[110],"that":[111],"the":[112,167],"significantly":[115],"outperforms":[116],"LSTM":[118],"CNN-LSTM":[120],"models":[121],"in":[122,129,173],"terms":[123],"accuracy":[125],"robustness,":[127],"particularly":[128],"handling":[130],"non-periodic":[131],"actions":[132],"such":[133],"crossing.":[136],"high":[140],"performance":[141],"by":[142],"effectively":[143],"fusing":[144],"adaptively":[147],"focusing":[148],"on":[149],"key":[150],"features,":[151],"enabling":[152],"it":[153],"to":[154],"maintain":[155],"robustness":[156],"even":[157],"under":[158],"noisy":[159],"conditions":[160],"significant":[162],"individual":[163],"differences.":[164],"demonstrates":[166],"model\u2019s":[168],"broad":[169],"application":[170],"potential,":[171],"especially":[172],"rehabilitation":[174],"prosthetic":[176],"control":[177],"systems.":[178]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-11-28T00:00:00"}