{"id":"https://openalex.org/W7171622464","doi":"https://doi.org/10.48550/arxiv.2607.25710","title":"Impact Detection in Fall Events: Leveraging Spatio-Temporal Graph Convolutional Networks and Recurrent Neural Networks Using 3D Skeletons Data","display_name":"Impact Detection in Fall Events: Leveraging Spatio-Temporal Graph Convolutional Networks and Recurrent Neural Networks Using 3D Skeletons Data","publication_year":2026,"publication_date":"2026-07-28","ids":{"openalex":"https://openalex.org/W7171622464","doi":"https://doi.org/10.48550/arxiv.2607.25710"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.25710","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.25710","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.25710","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037893683","display_name":"Tresor Y. Koffi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Koffi, Tresor Y.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049229616","display_name":"Youssef Mourchid","orcid":"https://orcid.org/0000-0003-4108-4557"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mourchid, Youssef","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132648658","display_name":"Mohammed Hindawi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hindawi, Mohammed","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5018852344","display_name":"Yohan Dupuis","orcid":"https://orcid.org/0000-0002-9725-2049"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dupuis, Yohan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.795799970626831,"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":0.795799970626831,"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/T10114","display_name":"Balance, Gait, and Falls Prevention","score":0.07680000364780426,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.04190000146627426,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5819000005722046},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.551800012588501},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.45820000767707825},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4465999901294708},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3555000126361847},{"id":"https://openalex.org/keywords/attention-network","display_name":"Attention network","score":0.34290000796318054}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7504000067710876},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5819000005722046},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.551800012588501},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5397999882698059},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.45820000767707825},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4465999901294708},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39419999718666077},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39160001277923584},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3555000126361847},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.34290000796318054},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30799999833106995},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.2849000096321106},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.259799987077713}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.25710","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.25710","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.25710","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.25710","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Fall":[0],"represents":[1],"a":[2,14,26,87],"significant":[3],"risk":[4],"of":[5],"accidental":[6],"death":[7],"among":[8],"individuals":[9],"aged":[10],"over":[11],"65,":[12],"presenting":[13],"global":[15],"health":[16],"concern.":[17],"A":[18],"fall":[19,51,77,144],"is":[20],"defined":[21],"as":[22,86],"any":[23],"event":[24],"where":[25,44],"person":[27,46],"loses":[28],"balance":[29],"and":[30,99,119],"moves":[31],"to":[32,123,156],"an":[33,42,69],"off-position,":[34],"which":[35],"may":[36,38],"or":[37],"not":[39],"result":[40],"in":[41,58],"impact":[43,60,108],"the":[45,48,132],"hits":[47],"ground.":[49],"While":[50],"detection":[52,61],"systems":[53],"have":[54,147],"achieved":[55],"good":[56],"results":[57],"general,":[59],"within":[62,76],"falls":[63,118],"remains":[64],"challenging.":[65],"This":[66],"study":[67],"proposes":[68],"efficient":[70],"methodology":[71],"for":[72],"accurately":[73],"detecting":[74],"impacts":[75],"events":[78],"by":[79,114],"incorporating":[80],"3D":[81,134],"joints":[82],"skeleton":[83],"data":[84],"treated":[85],"graph":[88],"using":[89,131],"Spatio-Temporal":[90],"Graph":[91],"Convolutional":[92],"Networks":[93],"(STGCN),":[94],"Gated":[95],"Recurrent":[96],"Unit":[97],"(GRU),":[98],"Bidirectional":[100],"Long":[101],"Short-Term":[102],"Memory":[103],"(BiLSTM)":[104],"layers.":[105],"By":[106],"pinpointing":[107],"moments,":[109],"our":[110],"approach":[111],"enhances":[112],"precision":[113],"distinguishing":[115],"between":[116],"false":[117],"actual":[120],"impacts,":[121],"contributing":[122],"better":[124],"healthcare":[125],"resource":[126],"allocation.":[127],"Our":[128],"methodology,":[129],"evaluated":[130],"improved":[133,150],"skeletons":[135],"UP-Fall":[136],"dataset,":[137],"achieves":[138],"accuracy":[139],"exceeding":[140],"90\\%":[141],"across":[142],"various":[143],"scenarios.":[145],"We":[146],"made":[148],"this":[149],"dataset":[151],"publicly":[152],"available":[153],"at":[154],"https://zenodo.org/records/12773013":[155],"facilitate":[157],"further":[158],"research.":[159]},"counts_by_year":[],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2026-07-30T00:00:00"}