{"id":"https://openalex.org/W7125952865","doi":"https://doi.org/10.1109/smc58881.2025.11343676","title":"EchoFall: An Indoor Acoustic Fall Detection and Severity Analysis Method","display_name":"EchoFall: An Indoor Acoustic Fall Detection and Severity Analysis Method","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125952865","doi":"https://doi.org/10.1109/smc58881.2025.11343676"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11343676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5124072996","display_name":"Rui Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rui Zhou","raw_affiliation_strings":["University of Electronic Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121800904","display_name":"Chenxu Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenxu Liu","raw_affiliation_strings":["University of Electronic Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047802436","display_name":"Jiajun Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajun Sun","raw_affiliation_strings":["University of Electronic Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124078272","display_name":"Songlin Li","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Songlin Li","raw_affiliation_strings":["University of Electronic Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5124072996"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.71700271,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7632","last_page":"7638"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.7185999751091003,"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":0.7185999751091003,"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":0.10199999809265137,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.020099999383091927,"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/spectrogram","display_name":"Spectrogram","score":0.8064000010490417},{"id":"https://openalex.org/keywords/confusion","display_name":"Confusion","score":0.6362000107765198},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5968000292778015},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.48159998655319214},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45989999175071716},{"id":"https://openalex.org/keywords/doppler-effect","display_name":"Doppler effect","score":0.4575999975204468},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4456999897956848}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.8064000010490417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6976000070571899},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.6362000107765198},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5968000292778015},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.48159998655319214},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45989999175071716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4593999981880188},{"id":"https://openalex.org/C142757262","wikidata":"https://www.wikidata.org/wiki/Q76436","display_name":"Doppler effect","level":2,"score":0.4575999975204468},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4456999897956848},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.4198000133037567},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3637000024318695},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3314000070095062},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.3116999864578247},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.28360000252723694},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.28029999136924744},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11343676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1976730168","https://openalex.org/W1982021240","https://openalex.org/W2028656089","https://openalex.org/W2076885544","https://openalex.org/W2121594589","https://openalex.org/W2128628418","https://openalex.org/W2164086816","https://openalex.org/W2166061769","https://openalex.org/W2169138660","https://openalex.org/W2194775991","https://openalex.org/W2338892592","https://openalex.org/W2343389358","https://openalex.org/W2783857023","https://openalex.org/W2783985400","https://openalex.org/W2971424155","https://openalex.org/W2997932427","https://openalex.org/W3034620145","https://openalex.org/W3093489396","https://openalex.org/W3115481010","https://openalex.org/W3201152140","https://openalex.org/W3201513527","https://openalex.org/W3203023227","https://openalex.org/W4284884132","https://openalex.org/W4285300395","https://openalex.org/W4286655986","https://openalex.org/W4310350092","https://openalex.org/W4312313324","https://openalex.org/W4361760217"],"related_works":[],"abstract_inverted_index":{"Fall":[0],"detection":[1,33,146],"is":[2],"of":[3,22,110,127,136,148],"significant":[4],"importance":[5],"for":[6],"healthcare.":[7],"However,":[8],"such":[9],"systems":[10],"still":[11],"suffer":[12],"from":[13,46,116],"confusion":[14],"with":[15],"fall-like":[16],"motions,":[17,48,56],"domain":[18,75,90],"dependence":[19],"and":[20,34,70,88,132,151,153],"lack":[21],"severity":[23,35,109,135],"analysis.":[24],"In":[25],"this":[26],"paper,":[27],"we":[28,77],"propose":[29],"an":[30],"acoustic":[31,40,122],"fall":[32,145],"analysis":[36],"method\u2014EchoFall,":[37],"leveraging":[38],"inaudible":[39],"signals.":[41],"To":[42,73,106],"distinguish":[43],"various":[44],"falls":[45,157],"daily":[47],"EchoFall":[49,112,142],"captures":[50],"the":[51,63,85,89,95,100,108,114,117,121,125,128,134,156],"Doppler":[52,58],"effect":[53],"induced":[54],"by":[55],"generates":[57],"Frequency":[59],"Spectrogram":[60],"(DFS),":[61],"employs":[62],"Residual":[64],"Network":[65],"(ResNet)":[66],"to":[67,83,97,103,120],"identify":[68,104,155],"sudden":[69],"soft":[71],"falls.":[72,105,137],"achieve":[74,144],"independence,":[76],"devise":[78],"a":[79],"feature":[80],"disentanglement":[81],"network":[82],"separate":[84],"motion":[86,101],"features":[87,91,102],"in":[92],"DFS,":[93],"allowing":[94],"classifier":[96],"take":[98],"only":[99],"analyze":[107],"falls,":[111],"estimates":[113],"distance":[115],"target":[118],"person":[119,129],"device,":[123],"monitors":[124],"status":[126],"after":[130],"fall,":[131],"identifies":[133],"Extensive":[138],"evaluations":[139],"demonstrate":[140],"that":[141],"can":[143,154],"independent":[147],"users,":[149],"locations":[150],"environments,":[152],"as":[158],"fatal,":[159],"moderate":[160],"or":[161],"minor,":[162],"facilitating":[163],"appropriate":[164],"rescues.":[165]},"counts_by_year":[],"updated_date":"2026-01-29T23:17:01.242718","created_date":"2026-01-29T00:00:00"}