{"id":"https://openalex.org/W4392158726","doi":"https://doi.org/10.1109/globecom54140.2023.10437886","title":"A Novel Approach for Activity, Fall and Gait Detection Using Multiple 2D LiDARs","display_name":"A Novel Approach for Activity, Fall and Gait Detection Using Multiple 2D LiDARs","publication_year":2023,"publication_date":"2023-12-04","ids":{"openalex":"https://openalex.org/W4392158726","doi":"https://doi.org/10.1109/globecom54140.2023.10437886"},"language":"en","primary_location":{"id":"doi:10.1109/globecom54140.2023.10437886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom54140.2023.10437886","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2023 - 2023 IEEE Global Communications Conference","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/A5068994330","display_name":"Mondher Bouazizi","orcid":"https://orcid.org/0000-0001-7055-9318"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Mondher Bouazizi","raw_affiliation_strings":["Keio University,Faculty of Science and Technology,Department of Information and Computer Science","Department of Information and Computer Science, Faculty of Science and Technology, Keio University"],"affiliations":[{"raw_affiliation_string":"Keio University,Faculty of Science and Technology,Department of Information and Computer Science","institution_ids":["https://openalex.org/I203951103"]},{"raw_affiliation_string":"Department of Information and Computer Science, Faculty of Science and Technology, Keio University","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093339745","display_name":"Kevin Feghoul","orcid":null},"institutions":[{"id":"https://openalex.org/I3018718406","display_name":"Centre Hospitalier Universitaire de Lille","ror":"https://ror.org/02ppyfa04","country_code":"FR","type":"funder","lineage":["https://openalex.org/I3018718406"]},{"id":"https://openalex.org/I154526488","display_name":"Inserm","ror":"https://ror.org/02vjkv261","country_code":"FR","type":"funder","lineage":["https://openalex.org/I154526488"]},{"id":"https://openalex.org/I2279609970","display_name":"Universit\u00e9 de Lille","ror":"https://ror.org/02kzqn938","country_code":"FR","type":"education","lineage":["https://openalex.org/I2279609970"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Kevin Feghoul","raw_affiliation_strings":["Univ. Lille, Inserm, CHU Lille, UMR-S1172 - LilNCog,Lille,France,F-59000"],"affiliations":[{"raw_affiliation_string":"Univ. Lille, Inserm, CHU Lille, UMR-S1172 - LilNCog,Lille,France,F-59000","institution_ids":["https://openalex.org/I154526488","https://openalex.org/I2279609970","https://openalex.org/I3018718406"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094002925","display_name":"Alejandro Lorite","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Alejandro Lorite","raw_affiliation_strings":["Graduate School of Science and Technology, Keio University Yokohama,Japan","Graduate School of Science and Technology, Keio University Yokohama, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University Yokohama,Japan","institution_ids":["https://openalex.org/I203951103"]},{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University Yokohama, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016337773","display_name":"Tomoaki Ohtsuki","orcid":"https://orcid.org/0000-0003-3961-1426"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoaki Ohtsuki","raw_affiliation_strings":["Keio University,Faculty of Science and Technology,Department of Information and Computer Science","Department of Information and Computer Science, Faculty of Science and Technology, Keio University"],"affiliations":[{"raw_affiliation_string":"Keio University,Faculty of Science and Technology,Department of Information and Computer Science","institution_ids":["https://openalex.org/I203951103"]},{"raw_affiliation_string":"Department of Information and Computer Science, Faculty of Science and Technology, Keio University","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5068994330"],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":null,"apc_paid":null,"fwci":0.3704,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.62406713,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1997","last_page":"2002"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9980000257492065,"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":0.9980000257492065,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9972000122070312,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.991599977016449,"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/lidar","display_name":"Lidar","score":0.6714524626731873},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.6601492762565613},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.644323468208313},{"id":"https://openalex.org/keywords/gait-analysis","display_name":"Gait analysis","score":0.47495031356811523},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42876285314559937},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40337038040161133},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3083309829235077},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.29541829228401184},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.10464534163475037},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.09658169746398926}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.6714524626731873},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.6601492762565613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.644323468208313},{"id":"https://openalex.org/C173906292","wikidata":"https://www.wikidata.org/wiki/Q1493441","display_name":"Gait analysis","level":3,"score":0.47495031356811523},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42876285314559937},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40337038040161133},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3083309829235077},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.29541829228401184},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.10464534163475037},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.09658169746398926}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom54140.2023.10437886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom54140.2023.10437886","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2023 - 2023 IEEE Global Communications Conference","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":18,"referenced_works":["https://openalex.org/W2009504845","https://openalex.org/W2774674002","https://openalex.org/W2781337562","https://openalex.org/W2796096089","https://openalex.org/W2909608117","https://openalex.org/W2956548091","https://openalex.org/W2971856312","https://openalex.org/W2983384859","https://openalex.org/W3008669640","https://openalex.org/W3014402465","https://openalex.org/W3163197578","https://openalex.org/W3213023270","https://openalex.org/W4210410362","https://openalex.org/W4213098855","https://openalex.org/W4221102521","https://openalex.org/W4281262639","https://openalex.org/W4296627087","https://openalex.org/W6758065289"],"related_works":["https://openalex.org/W2351984678","https://openalex.org/W2140032575","https://openalex.org/W2011860471","https://openalex.org/W2012196540","https://openalex.org/W3011451421","https://openalex.org/W2133973503","https://openalex.org/W2471060339","https://openalex.org/W2148547327","https://openalex.org/W4226236273","https://openalex.org/W2125892956"],"abstract_inverted_index":{"A":[0,54],"key":[1],"concept":[2],"in":[3,36,103,114],"health":[4],"monitoring":[5],"systems":[6],"for":[7,91],"elderly":[8],"people":[9],"is":[10,63],"the":[11,37,41,64,122,129,132,158],"continuous":[12],"and":[13,87,112,169,183],"non-intrusive":[14],"detection":[15,42,49],"of":[16,34,44,47,66,121,131],"their":[17],"activities":[18,123],"to":[19,30,59,116,156,180],"identify":[20],"when":[21],"hazardous":[22],"events":[23],"such":[24],"as":[25],"sudden":[26],"falling":[27],"occur/are":[28],"about":[29],"occur.":[31],"The":[32,144],"existence":[33],"obstacles":[35,109],"environment":[38],"largely":[39],"limits":[40],"performance":[43],"existing":[45],"approaches":[46],"activity":[48,92,165],"relying":[50],"on":[51,83],"non-contact":[52],"sensors.":[53],"simple,":[55],"yet":[56],"effective,":[57],"approach":[58,80,127,175],"address":[60],"this":[61,75],"issue":[62],"use":[65],"multiple":[67,96],"sensors":[68],"which":[69],"collaborate":[70],"with":[71,107],"one":[72],"another.":[73],"In":[74],"paper,":[76],"we":[77],"propose":[78],"an":[79,177],"that":[81],"relies":[82],"2D":[84,97],"Light":[85],"Detection":[86],"Ranging":[88],"(LiDAR)":[89],"technology":[90],"detection.":[93],"We":[94],"employ":[95],"LiDARs":[98],"placed":[99],"at":[100],"different":[101,133,162],"locations":[102],"a":[104,118,137,151],"single":[105],"room":[106],"difference":[108],"(e.g.,":[110],"furniture)":[111],"working":[113],"coordination":[115],"construct":[117],"fuller":[119],"representation":[120],"being":[124],"performed.":[125],"Our":[126],"transforms":[128],"concatenation":[130],"LiDAR":[134],"data":[135,140],"into":[136],"more":[138],"comprehensible":[139],"format":[141],"(i.e.,":[142],"images).":[143],"generated":[145],"images":[146],"are":[147],"then":[148],"processed":[149],"using":[150],"Convolutional":[152],"LSTM":[153],"Neural":[154],"Network":[155],"perform":[157],"classification.":[159],"For":[160],"3":[161],"tasks,":[163],"namely":[164],"detection,":[166,168,172],"fall":[167],"unsteady":[170],"gate":[171],"our":[173],"proposed":[174],"reaches":[176],"accuracy":[178],"equal":[179],"96.10%,":[181],"99.13%":[182],"93.13%,":[184],"respectively.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
