{"id":"https://openalex.org/W3118583822","doi":"https://doi.org/10.1109/siu49456.2020.9302065","title":"Contactless Fall Detection using Doppler Radar","display_name":"Contactless Fall Detection using Doppler Radar","publication_year":2020,"publication_date":"2020-10-05","ids":{"openalex":"https://openalex.org/W3118583822","doi":"https://doi.org/10.1109/siu49456.2020.9302065","mag":"3118583822"},"language":"en","primary_location":{"id":"doi:10.1109/siu49456.2020.9302065","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu49456.2020.9302065","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 28th Signal Processing and Communications Applications Conference (SIU)","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/A5063689765","display_name":"Khadija Hanifi","orcid":"https://orcid.org/0000-0001-7044-3315"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khadija Hanifi","raw_affiliation_strings":["Ak&#x0131;ll&#x0131; Sistemler Laboratuvar&#x0131;, Bilgisayar M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;, Y&#x0131;ld&#x0131;z Teknik &#x00DC;niversitesi,&#x0130;stanbul,T&#x00FC;rkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ak&#x0131;ll&#x0131; Sistemler Laboratuvar&#x0131;, Bilgisayar M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;, Y&#x0131;ld&#x0131;z Teknik &#x00DC;niversitesi,&#x0130;stanbul,T&#x00FC;rkiye","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056353753","display_name":"M. Elif Karsl\u0131gil","orcid":"https://orcid.org/0000-0002-3477-582X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"M.Elif Karslig\u0131l","raw_affiliation_strings":["Ak&#x0131;ll&#x0131; Sistemler Laboratuvar&#x0131;, Bilgisayar M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;, Y&#x0131;ld&#x0131;z Teknik &#x00DC;niversitesi,&#x0130;stanbul,T&#x00FC;rkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ak&#x0131;ll&#x0131; Sistemler Laboratuvar&#x0131;, Bilgisayar M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;, Y&#x0131;ld&#x0131;z Teknik &#x00DC;niversitesi,&#x0130;stanbul,T&#x00FC;rkiye","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.15299246,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9988999962806702,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9988999962806702,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9850000143051147,"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":0.9455000162124634,"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/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.8059161901473999},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6607577204704285},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6603389978408813},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6429256200790405},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5980451107025146},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5784574747085571},{"id":"https://openalex.org/keywords/doppler-radar","display_name":"Doppler radar","score":0.5624128580093384},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5400631427764893},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5246567726135254},{"id":"https://openalex.org/keywords/falling","display_name":"Falling (accident)","score":0.43938392400741577},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10717472434043884}],"concepts":[{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.8059161901473999},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6607577204704285},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6603389978408813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6429256200790405},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5980451107025146},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5784574747085571},{"id":"https://openalex.org/C2778559676","wikidata":"https://www.wikidata.org/wiki/Q1334213","display_name":"Doppler radar","level":3,"score":0.5624128580093384},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5400631427764893},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5246567726135254},{"id":"https://openalex.org/C2779079380","wikidata":"https://www.wikidata.org/wiki/Q333495","display_name":"Falling (accident)","level":2,"score":0.43938392400741577},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10717472434043884},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu49456.2020.9302065","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu49456.2020.9302065","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 28th Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1762680893","https://openalex.org/W1967689064","https://openalex.org/W2018282406","https://openalex.org/W2022102190","https://openalex.org/W2039891177","https://openalex.org/W2050534580","https://openalex.org/W2063982587","https://openalex.org/W2064713387","https://openalex.org/W2075937999","https://openalex.org/W2109142006","https://openalex.org/W2133140997","https://openalex.org/W2134050473","https://openalex.org/W2170070423","https://openalex.org/W2227813149","https://openalex.org/W2298692413","https://openalex.org/W2407689736","https://openalex.org/W3000189524","https://openalex.org/W3097993951","https://openalex.org/W3154732924"],"related_works":["https://openalex.org/W2746852369","https://openalex.org/W4389954502","https://openalex.org/W2771255398","https://openalex.org/W2930428186","https://openalex.org/W3200027047","https://openalex.org/W4385770464","https://openalex.org/W3125536479","https://openalex.org/W3120363735","https://openalex.org/W4214820172","https://openalex.org/W2394323384"],"abstract_inverted_index":{"Falling":[0],"is":[1,25,51,97],"the":[2,8,100],"main":[3],"cause":[4],"of":[5,10,42],"disability":[6],"and":[7,33,48,53,62,92],"fatality":[9],"elderly.":[11],"In":[12],"this":[13],"work,":[14],"a":[15,28],"24":[16],"GHz":[17],"continuous":[18],"wave":[19],"(CW)":[20],"Doppler":[21],"Radar-based":[22],"novel":[23],"system":[24,107],"proposed":[26,106],"as":[27,99],"cheap,":[29],"easy":[30],"to":[31,58],"use":[32],"effective":[34],"solution":[35],"for":[36],"elderly":[37],"fall":[38,61,109],"detection.":[39],"A":[40],"set":[41],"features":[43,54],"extracted":[44],"from":[45],"both":[46],"time":[47],"frequency":[49],"domains":[50],"examined":[52],"that":[55],"contribute":[56],"most":[57,101],"distinguish":[59],"between":[60],"non-fall":[63],"samples":[64],"are":[65,90],"selected.":[66],"Finally,":[67],"different":[68],"learning":[69],"techniques":[70],"including":[71],"support":[72],"vector":[73],"machine":[74],"(SVM),":[75],"k":[76],"nearest":[77],"neighborhood":[78],"(kNN),":[79],"Na\u00efve":[80],"Bayes":[81],"(NB),":[82],"linear":[83,93],"discriminant":[84,94],"analysis":[85,95],"(LDA)and":[86],"decision":[87],"tree":[88],"(DT)":[89],"evaluated":[91],"method":[96],"selected":[98],"accurate":[102],"classification":[103],"model.":[104],"The":[105],"performed":[108],"detection":[110],"with":[111],"88%":[112],"accuracy.":[113]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
