{"id":"https://openalex.org/W7167057506","doi":"https://doi.org/10.1109/percomworkshops68308.2026.11585318","title":"Radar-Based Fall Detection for Assisted Living: A Digital-Twin Representation Case Study","display_name":"Radar-Based Fall Detection for Assisted Living: A Digital-Twin Representation Case Study","publication_year":2026,"publication_date":"2026-03-16","ids":{"openalex":"https://openalex.org/W7167057506","doi":"https://doi.org/10.1109/percomworkshops68308.2026.11585318"},"language":null,"primary_location":{"id":"doi:10.1109/percomworkshops68308.2026.11585318","is_oa":false,"landing_page_url":"https://doi.org/10.1109/percomworkshops68308.2026.11585318","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2601.11938","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119317437","display_name":"Sebastian Ratto","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sebastian Ratto V","raw_affiliation_strings":["University of Waterloo,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo,Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133063273","display_name":"Huy Trinh","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Huy Trinh","raw_affiliation_strings":["University of Waterloo,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo,Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089871700","display_name":"Ahmed N. Sayed","orcid":"https://orcid.org/0000-0003-3821-0487"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ahmed N. Sayed","raw_affiliation_strings":["University of Waterloo,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo,Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5095877937","display_name":"Abdelrahman Elbadrawy","orcid":"https://orcid.org/0009-0005-2533-3973"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Abdelrahman Elbadrawy","raw_affiliation_strings":["University of Waterloo,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo,Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138178893","display_name":"Arien Sligar","orcid":null},"institutions":[{"id":"https://openalex.org/I4210088951","display_name":"Synopsys (United States)","ror":"https://ror.org/013by2m91","country_code":"US","type":"company","lineage":["https://openalex.org/I4210088951"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arien Sligar","raw_affiliation_strings":["Synopsys Inc.,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Synopsys Inc.,USA","institution_ids":["https://openalex.org/I4210088951"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5139897918","display_name":"George Shaker","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"George Shaker","raw_affiliation_strings":["University of Waterloo,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo,Canada","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.93561131,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.14259999990463257,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.14259999990463257,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.07699999958276749,"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":0.07180000096559525,"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/representation","display_name":"Representation (politics)","score":0.4629000127315521},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3264999985694885},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3001999855041504},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.289900004863739},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.25529998540878296}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5534999966621399},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5526999831199646},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4629000127315521},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3939000070095062},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.289900004863739},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22930000722408295},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.21930000185966492}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/percomworkshops68308.2026.11585318","is_oa":false,"landing_page_url":"https://doi.org/10.1109/percomworkshops68308.2026.11585318","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2601.11938","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2601.11938","pdf_url":"https://arxiv.org/pdf/2601.11938","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2601.11938","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2601.11938","pdf_url":"https://arxiv.org/pdf/2601.11938","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5","score":0.4655628204345703}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310709","display_name":"CMC Microsystems","ror":"https://ror.org/03k70ea39"},{"id":"https://openalex.org/F4320322675","display_name":"Mitacs","ror":"https://ror.org/00cjrc276"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Obtaining":[0],"data":[1],"on":[2,29,101],"high-impact":[3],"falls":[4,31],"from":[5,32,45],"older":[6],"adults":[7],"is":[8,184],"ethically":[9],"difficult,":[10],"yet":[11],"these":[12,193],"rare":[13],"events":[14],"cause":[15],"many":[16],"fall-related":[17],"health":[18],"problems.":[19],"As":[20],"a":[21,51,59,102,189],"result,":[22],"most":[23],"radar-based":[24],"fall":[25,145],"detectors":[26],"are":[27,38,89],"trained":[28],"staged":[30],"young":[33],"volunteers,":[34],"and":[35,84,91,118,128,143,180,183],"representation":[36,67],"choices":[37],"rarely":[39],"tested":[40],"against":[41],"the":[42,73,135,149,161,173,176],"radar":[43,55],"signals":[44],"dangerous":[46],"falls.":[47],"This":[48],"paper":[49],"uses":[50],"frequency-modulated":[52],"continuous-wave":[53],"(FMCW)":[54],"digital":[56],"twin":[57,150,177],"as":[58],"single":[60,190],"simulated":[61,75],"room":[62],"testbed":[63],"to":[64,93,188],"study":[65],"how":[66],"choice":[68],"affects":[69],"fall/non-fall":[70,104],"discrimination.":[71],"From":[72],"same":[74,136],"range-Doppler":[76,86],"sequence,":[77],"Doppler-time":[78,153],"spectrograms,":[79],"three-channel":[80],"per-receiver":[81],"spectrogram":[82],"stacks,":[83],"time-pooled":[85],"maps":[87],"(RDMs)":[88],"derived":[90],"fed":[92],"an":[94],"identical":[95],"compact":[96],"CNN":[97],"under":[98,198],"matched":[99],"training":[100,132],"balanced":[103],"dataset.":[105],"In":[106],"this":[107],"twin,":[108],"temporal":[109],"spectrograms":[110,146],"reach":[111,126],"98-99%":[112],"test":[113],"accuracy":[114],"with":[115,167],"similar":[116],"precision":[117],"recall":[119],"for":[120],"both":[121],"classes,":[122],"while":[123],"static":[124],"RDMs":[125],"89.4%":[127],"show":[129],"more":[130],"variable":[131],"despite":[133],"using":[134],"backbone.":[137],"A":[138],"qualitative":[139],"comparison":[140],"between":[141],"synthetic":[142,200],"measured":[144,191],"suggests":[147],"that":[148],"captures":[151],"gross":[152],"structure,":[154],"but":[155],"amplitude":[156,164],"histograms":[157],"reveal":[158],"differences":[159],"in":[160,172,207],"distributions":[162],"of":[163],"values":[165],"consistent":[166],"receiver":[168],"processing":[169],"not":[170],"modeled":[171],"twin.":[174],"Because":[175],"omits":[178],"noise":[179],"hardware":[181],"impairments":[182],"only":[185],"qualitatively":[186],"compared":[187],"example,":[192],"results":[194],"provide":[195],"representation-level":[196],"guidance":[197],"controlled":[199],"conditions":[201],"rather":[202],"than":[203],"ready-to-use":[204],"clinical":[205],"performance":[206],"real":[208],"settings.":[209]},"counts_by_year":[],"updated_date":"2026-07-10T07:45:09.275182","created_date":"2026-07-03T00:00:00"}
