{"id":"https://openalex.org/W4401113876","doi":"https://doi.org/10.1109/ict62760.2024.10606132","title":"Improving Fall Detection Systems Performance via Skeleton Topology Selection by using Graph Convolution Neural Networks","display_name":"Improving Fall Detection Systems Performance via Skeleton Topology Selection by using Graph Convolution Neural Networks","publication_year":2024,"publication_date":"2024-06-24","ids":{"openalex":"https://openalex.org/W4401113876","doi":"https://doi.org/10.1109/ict62760.2024.10606132"},"language":"en","primary_location":{"id":"doi:10.1109/ict62760.2024.10606132","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ict62760.2024.10606132","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 30th International Conference on Telecommunications (ICT)","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/A5036299185","display_name":"Motasem S. Alsawadi","orcid":null},"institutions":[{"id":"https://openalex.org/I1284598098","display_name":"King Abdulaziz City for Science and Technology","ror":"https://ror.org/05tdz6m39","country_code":"SA","type":"facility","lineage":["https://openalex.org/I1284598098"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Motasem S. Alsawadi","raw_affiliation_strings":["Institute of Next Generation Connectivity King Abdulaziz City for Science and Technology (KACST),Riyadh,Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"Institute of Next Generation Connectivity King Abdulaziz City for Science and Technology (KACST),Riyadh,Saudi Arabia","institution_ids":["https://openalex.org/I1284598098"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050635142","display_name":"Saleh Almarshed","orcid":"https://orcid.org/0000-0002-4776-3553"},"institutions":[{"id":"https://openalex.org/I1284598098","display_name":"King Abdulaziz City for Science and Technology","ror":"https://ror.org/05tdz6m39","country_code":"SA","type":"facility","lineage":["https://openalex.org/I1284598098"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Saleh A Almarshed","raw_affiliation_strings":["Institute of Next Generation Connectivity King Abdulaziz City for Science and Technology (KACST),Riyadh,Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"Institute of Next Generation Connectivity King Abdulaziz City for Science and Technology (KACST),Riyadh,Saudi Arabia","institution_ids":["https://openalex.org/I1284598098"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5036299185"],"corresponding_institution_ids":["https://openalex.org/I1284598098"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11128747,"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":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.8863999843597412,"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":0.8863999843597412,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8058000206947327,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12740","display_name":"Gait Recognition and Analysis","score":0.7950999736785889,"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/computer-science","display_name":"Computer science","score":0.7029790878295898},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6502155065536499},{"id":"https://openalex.org/keywords/skeleton","display_name":"Skeleton (computer programming)","score":0.6194020509719849},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.5305861234664917},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5270355343818665},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5253214836120605},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4583406448364258},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4168066382408142},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34416893124580383},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.25327908992767334},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20764762163162231}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7029790878295898},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6502155065536499},{"id":"https://openalex.org/C18969341","wikidata":"https://www.wikidata.org/wiki/Q1169129","display_name":"Skeleton (computer programming)","level":2,"score":0.6194020509719849},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.5305861234664917},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5270355343818665},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5253214836120605},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4583406448364258},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4168066382408142},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34416893124580383},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25327908992767334},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20764762163162231},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ict62760.2024.10606132","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ict62760.2024.10606132","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 30th International Conference on Telecommunications (ICT)","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":16,"referenced_works":["https://openalex.org/W2952122856","https://openalex.org/W2962134292","https://openalex.org/W2962730651","https://openalex.org/W2963076818","https://openalex.org/W2963781481","https://openalex.org/W2964134613","https://openalex.org/W3152893301","https://openalex.org/W3188254839","https://openalex.org/W4207081826","https://openalex.org/W4240620948","https://openalex.org/W4287755748","https://openalex.org/W4291926315","https://openalex.org/W4389626868","https://openalex.org/W4392741075","https://openalex.org/W6765401191","https://openalex.org/W6779739588"],"related_works":["https://openalex.org/W2953562271","https://openalex.org/W2334655667","https://openalex.org/W2464530384","https://openalex.org/W2105938841","https://openalex.org/W4253358700","https://openalex.org/W3139863978","https://openalex.org/W2014897006","https://openalex.org/W1756135943","https://openalex.org/W4247976907","https://openalex.org/W4388657984"],"abstract_inverted_index":{"This":[0],"paper":[1],"evaluates":[2],"the":[3,41,46,88,92,98],"performance":[4,99],"of":[5,70,90,100],"three":[6],"popular":[7],"skeleton":[8,94],"formats":[9],"specifically":[10],"for":[11,72,80],"fall":[12,73,101],"detection:":[13],"OpenPose,":[14],"BlazePose,":[15],"and":[16,27,34,57,78,82],"AlphaPose.":[17],"The":[18],"study":[19],"employs":[20],"a":[21],"two-stream":[22],"architecture":[23],"that":[24,50,65],"combines":[25],"skeletal":[26],"RGB":[28],"data":[29],"to":[30,76,96],"capture":[31],"both":[32],"spatial":[33],"temporal":[35],"features,":[36],"improving":[37],"prediction":[38],"accuracy.":[39],"Using":[40],"Le2i":[42],"Fall":[43],"Detection":[44],"Dataset,":[45],"experimental":[47],"results":[48,63,86],"show":[49,64],"OpenPose":[51,66],"consistently":[52],"performs":[53],"better":[54],"than":[55],"BlazePose":[56,81],"AlphaPose":[58],"in":[59],"detecting":[60],"falls.":[61],"Our":[62],"achieves":[67],"an":[68],"F1-score":[69],"84.50%":[71],"detection,":[74],"compared":[75],"74.60%":[77],"83.90%":[79],"AlphaPose,":[83],"respectively.":[84],"These":[85],"highlight":[87],"importance":[89],"choosing":[91],"right":[93],"topology":[95],"enhance":[97],"detection":[102],"systems.":[103]},"counts_by_year":[],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}