{"id":"https://openalex.org/W4416250249","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228465","title":"Cross-Graph Relational Knowledge Distillation with Lightweight ST-GCN for Gait Disorder Recognition","display_name":"Cross-Graph Relational Knowledge Distillation with Lightweight ST-GCN for Gait Disorder Recognition","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250249","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228465"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5120450537","display_name":"Zakariae Zrimek","orcid":null},"institutions":[{"id":"https://openalex.org/I126477371","display_name":"Mohammed V University","ror":"https://ror.org/00r8w8f84","country_code":"MA","type":"education","lineage":["https://openalex.org/I126477371"]}],"countries":["MA"],"is_corresponding":true,"raw_author_name":"Zakariae Zrimek","raw_affiliation_strings":["LRIT FSR, Mohammed V University in Rabat,Morocco"],"affiliations":[{"raw_affiliation_string":"LRIT FSR, Mohammed V University in Rabat,Morocco","institution_ids":["https://openalex.org/I126477371"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049229616","display_name":"Youssef Mourchid","orcid":"https://orcid.org/0000-0003-4108-4557"},"institutions":[{"id":"https://openalex.org/I4210155362","display_name":"Centre d'Etudes Superieures Industrielles","ror":"https://ror.org/04f87d812","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210155362"]},{"id":"https://openalex.org/I4210089119","display_name":"Cole Engineering Services (United States)","ror":"https://ror.org/009vrft62","country_code":"US","type":"company","lineage":["https://openalex.org/I4210089119"]}],"countries":["FR","US"],"is_corresponding":false,"raw_author_name":"Youssef Mourchid","raw_affiliation_strings":["CESI LINEACT, UR 7527 CESI,Dijon,France"],"affiliations":[{"raw_affiliation_string":"CESI LINEACT, UR 7527 CESI,Dijon,France","institution_ids":["https://openalex.org/I4210155362","https://openalex.org/I4210089119"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046609840","display_name":"Mohammed El Hassouni","orcid":"https://orcid.org/0000-0002-6741-4799"},"institutions":[{"id":"https://openalex.org/I126477371","display_name":"Mohammed V University","ror":"https://ror.org/00r8w8f84","country_code":"MA","type":"education","lineage":["https://openalex.org/I126477371"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Mohammed El Hassouni","raw_affiliation_strings":["LRIT FLSH, Mohammed V University in Rabat,Morocco"],"affiliations":[{"raw_affiliation_string":"LRIT FLSH, Mohammed V University in Rabat,Morocco","institution_ids":["https://openalex.org/I126477371"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5120450537"],"corresponding_institution_ids":["https://openalex.org/I126477371"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.3480574,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.6873000264167786,"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":0.6873000264167786,"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/T10114","display_name":"Balance, Gait, and Falls Prevention","score":0.1688999980688095,"subfield":{"id":"https://openalex.org/subfields/3612","display_name":"Physical Therapy, Sports Therapy and Rehabilitation"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.022099999710917473,"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":0.5321000218391418},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.513700008392334},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.40880000591278076},{"id":"https://openalex.org/keywords/movement","display_name":"Movement (music)","score":0.3953999876976013},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.3767000138759613},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37560001015663147},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.31139999628067017},{"id":"https://openalex.org/keywords/relational-model","display_name":"Relational model","score":0.30730000138282776}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6703000068664551},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5996000170707703},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.5321000218391418},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.513700008392334},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4797999858856201},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.40880000591278076},{"id":"https://openalex.org/C2780226923","wikidata":"https://www.wikidata.org/wiki/Q929848","display_name":"Movement (music)","level":2,"score":0.3953999876976013},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","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":0.37560001015663147},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31279999017715454},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.31139999628067017},{"id":"https://openalex.org/C40207289","wikidata":"https://www.wikidata.org/wiki/Q755662","display_name":"Relational model","level":3,"score":0.30730000138282776},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C173906292","wikidata":"https://www.wikidata.org/wiki/Q1493441","display_name":"Gait analysis","level":3,"score":0.2973000109195709},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2784999907016754},{"id":"https://openalex.org/C2780906641","wikidata":"https://www.wikidata.org/wiki/Q213373","display_name":"Ataxia","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2605000138282776},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.258899986743927}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-05367608v1","is_oa":false,"landing_page_url":"https://hal.science/hal-05367608","pdf_url":null,"source":{"id":"https://openalex.org/S4406922461","display_name":"SPIRE - Sciences Po Institutional REpository","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN), Jun 2025, Rome, Italy. pp.1-8, &#x27E8;10.1109/IJCNN64981.2025.11228465&#x27E9;","raw_type":"Conference papers"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2108344016","https://openalex.org/W2140513563","https://openalex.org/W2559085405","https://openalex.org/W2810052253","https://openalex.org/W3118216747","https://openalex.org/W3131579999","https://openalex.org/W3198180660","https://openalex.org/W4213267524","https://openalex.org/W4224267821","https://openalex.org/W4281651174","https://openalex.org/W4303954724","https://openalex.org/W4312309807","https://openalex.org/W4327520730","https://openalex.org/W4361761487","https://openalex.org/W4378078316","https://openalex.org/W4389474449","https://openalex.org/W4389474709","https://openalex.org/W4392361094","https://openalex.org/W4399901651","https://openalex.org/W4400340741","https://openalex.org/W4410949532"],"related_works":[],"abstract_inverted_index":{"Gait":[0],"recognition":[1],"is":[2],"essential":[3],"for":[4,76,135],"early":[5,18],"diagnosis":[6],"of":[7,12,20,162],"movement":[8,70,122],"disorders.":[9],"The":[10,155],"integration":[11],"new":[13],"technologies":[14],"can":[15],"enhance":[16],"the":[17,132,141,163],"identification":[19],"these":[21,38],"conditions.":[22],"Many":[23],"current":[24],"studies":[25],"use":[26,47],"Spatio-Temporal":[27],"Graph":[28],"Convolutional":[29],"Networks":[30],"(ST-GCN)":[31],"that":[32,59,90,148],"depend":[33],"on":[34,140],"skeletal":[35,115],"data,":[36],"however,":[37],"models":[39],"often":[40],"require":[41],"substantial":[42],"memory,":[43],"which":[44],"limits":[45],"their":[46],"in":[48],"clinical":[49,136],"settings.":[50],"This":[51],"work":[52],"introduces":[53],"an":[54],"improved":[55],"lightweight":[56],"ST-GCN":[57],"model":[58,101],"merges":[60],"temporal":[61,95],"convolution,":[62],"weighted":[63],"fusion,":[64],"and":[65,72,94,111,144],"GRU":[66],"units":[67],"to":[68,102],"analyze":[69],"patterns":[71],"extract":[73],"spatiotemporal":[74],"features":[75],"gait":[77],"classification.":[78],"Additionally,":[79],"we":[80],"present":[81],"a":[82,99,103],"novel":[83],"Cross-Graph":[84],"Relational":[85],"Knowledge":[86],"Distillation":[87],"(CGRKD)":[88],"technique":[89],"transfers":[91],"both":[92],"spatial":[93],"relationship":[96],"knowledge":[97],"from":[98],"larger":[100],"more":[104],"compact":[105],"one":[106],"by":[107],"using":[108],"shared":[109],"memory":[110],"relational":[112],"alignment":[113],"among":[114],"joints.":[116],"Our":[117],"CGRKD":[118],"approach":[119],"preserves":[120],"important":[121],"relationships":[123],"between":[124],"joints":[125],"while":[126],"lowering":[127],"computational":[128],"complexity,":[129],"thus":[130],"enhancing":[131],"model\u2019s":[133],"suitability":[134],"use.":[137],"Experimental":[138],"results":[139],"KOA-NM,":[142],"PD-WALK,":[143],"ATAXIA":[145],"datasets":[146],"indicate":[147],"our":[149],"method":[150],"surpasses":[151],"existing":[152],"literature":[153],"methods.":[154],"code":[156],"will":[157],"be":[158],"available":[159],"upon":[160],"acceptance":[161],"paper.":[164]},"counts_by_year":[],"updated_date":"2026-03-16T09:10:04.655348","created_date":"2025-11-14T00:00:00"}
