{"id":"https://openalex.org/W7125895859","doi":"https://doi.org/10.1109/smc58881.2025.11343077","title":"A Gait Stability Prediction Framework via Multi-Modal Fusion and BiLSTM-KAN for Treadmill Walking","display_name":"A Gait Stability Prediction Framework via Multi-Modal Fusion and BiLSTM-KAN for Treadmill Walking","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125895859","doi":"https://doi.org/10.1109/smc58881.2025.11343077"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11343077","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343077","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5122994755","display_name":"Xuan Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xuan Huang","raw_affiliation_strings":["Waseda University,Faculty of Human Sciences,Tokorozawa,Japan,359-1192"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Faculty of Human Sciences,Tokorozawa,Japan,359-1192","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124080701","display_name":"Bo Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I148798404","display_name":"Tokyo University of Technology","ror":"https://ror.org/021a26605","country_code":"JP","type":"education","lineage":["https://openalex.org/I148798404"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Bo Wu","raw_affiliation_strings":["Tokyo University of Technology,School of Computer Science,Tokyo,Japan,192-0982"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo University of Technology,School of Computer Science,Tokyo,Japan,192-0982","institution_ids":["https://openalex.org/I148798404"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043621115","display_name":"Shoji Nishimura","orcid":"https://orcid.org/0000-0001-5975-2002"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shoji Nishimura","raw_affiliation_strings":["Waseda University,Faculty of Human Sciences,Tokorozawa,Japan,359-1192"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Faculty of Human Sciences,Tokorozawa,Japan,359-1192","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.43140000104904175,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.43140000104904175,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.12780000269412994,"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/T11018","display_name":"Lower Extremity Biomechanics and Pathologies","score":0.10029999911785126,"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/gait","display_name":"Gait","score":0.6115000247955322},{"id":"https://openalex.org/keywords/safer","display_name":"SAFER","score":0.5849000215530396},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5357999801635742},{"id":"https://openalex.org/keywords/treadmill","display_name":"Treadmill","score":0.4551999866962433},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.430400013923645},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3970000147819519},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3797999918460846}],"concepts":[{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.6115000247955322},{"id":"https://openalex.org/C2776654903","wikidata":"https://www.wikidata.org/wiki/Q2601463","display_name":"SAFER","level":2,"score":0.5849000215530396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5641999840736389},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5357999801635742},{"id":"https://openalex.org/C2781464450","wikidata":"https://www.wikidata.org/wiki/Q839144","display_name":"Treadmill","level":2,"score":0.4551999866962433},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44940000772476196},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.430400013923645},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.40130001306533813},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3970000147819519},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3797999918460846},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34860000014305115},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.3456000089645386},{"id":"https://openalex.org/C168031717","wikidata":"https://www.wikidata.org/wiki/Q1530280","display_name":"Balance (ability)","level":2,"score":0.34470000863075256},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.3237000107765198},{"id":"https://openalex.org/C170700871","wikidata":"https://www.wikidata.org/wiki/Q193378","display_name":"Biomechanics","level":2,"score":0.31060001254081726},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C173906292","wikidata":"https://www.wikidata.org/wiki/Q1493441","display_name":"Gait analysis","level":3,"score":0.287200003862381},{"id":"https://openalex.org/C2776462017","wikidata":"https://www.wikidata.org/wiki/Q59744853","display_name":"Orthotics","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C2776516907","wikidata":"https://www.wikidata.org/wiki/Q5432181","display_name":"Fall prevention","level":4,"score":0.265500009059906},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.26269999146461487}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11343077","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343077","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2118869643","https://openalex.org/W2158764002","https://openalex.org/W2161765194","https://openalex.org/W2916798096","https://openalex.org/W2962730651","https://openalex.org/W3150750468","https://openalex.org/W3206418279","https://openalex.org/W4211044710","https://openalex.org/W4316928326","https://openalex.org/W4379985979","https://openalex.org/W4385331930","https://openalex.org/W4406570264"],"related_works":[],"abstract_inverted_index":{"With":[0],"increasing":[1],"public":[2],"attention":[3],"to":[4,22,61,70,80,100,122],"health":[5,177],"and":[6,67,75,147,175],"wellness,":[7],"treadmill":[8,27],"exercise":[9,174],"in":[10,138],"gyms":[11],"has":[12],"become":[13],"increasingly":[14],"popular.":[15],"However,":[16],"the":[17,82,86,120,132,152],"risk":[18,117],"of":[19,24,94,115,154],"falling":[20],"due":[21],"loss":[23],"balance":[25],"during":[26,126],"use":[28,59],"remains":[29],"a":[30,40,47,109,155,169],"significant":[31],"safety":[32],"concern.":[33],"To":[34],"address":[35],"this":[36],"issue,":[37],"we":[38,58],"propose":[39],"gait":[41,165],"stability":[42,102,166],"prediction":[43],"framework":[44],"that":[45,131],"leverages":[46],"deep":[48],"learning":[49],"neural":[50],"network":[51],"BiLSTM-KAN":[52],"trained":[53,90],"on":[54,104,161],"multimodal":[55,162],"data.":[56,88],"Specifically,":[57],"MediaPipe":[60],"extract":[62],"3D":[63],"skeletal":[64],"key":[65,140],"points":[66],"smart":[68],"insoles":[69],"capture":[71],"essential":[72],"plantar":[73,87],"features":[74,84],"then":[76],"perform":[77],"data":[78,106],"preprocessing":[79],"synchronize":[81],"postural":[83],"with":[85],"The":[89],"model":[91],"is":[92],"capable":[93],"predicting":[95,139],"15":[96],"biomechanical":[97],"indicators":[98],"related":[99],"foot":[101],"based":[103,160],"pose":[105],"obtained":[107],"from":[108],"camera,":[110],"thereby":[111],"enabling":[112],"indirect":[113],"assessment":[114],"fall":[116],"without":[118],"requiring":[119],"user":[121],"wear":[123],"any":[124],"devices":[125],"use.":[127],"Experimental":[128],"results":[129],"demonstrate":[130],"proposed":[133],"system":[134],"achieves":[135],"high":[136],"accuracy":[137],"stability-related":[141],"parameters":[142],"such":[143],"as":[144],"Gait-Line":[145],"CPE":[146],"Impulse.":[148],"This":[149],"study":[150],"validates":[151],"feasibility":[153],"non-contact,":[156],"continuous":[157],"monitoring":[158],"approach":[159],"fusion":[163],"for":[164,172],"assessment,":[167],"providing":[168],"practical":[170],"solution":[171],"safer":[173],"intelligent":[176],"monitoring.":[178]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-29T00:00:00"}