{"id":"https://openalex.org/W2344160634","doi":"https://doi.org/10.1109/healthcom.2015.7454538","title":"A fall detection system based on infrared array sensors with tracking capability for the elderly at home","display_name":"A fall detection system based on infrared array sensors with tracking capability for the elderly at home","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2344160634","doi":"https://doi.org/10.1109/healthcom.2015.7454538","mag":"2344160634"},"language":"en","primary_location":{"id":"doi:10.1109/healthcom.2015.7454538","is_oa":false,"landing_page_url":"https://doi.org/10.1109/healthcom.2015.7454538","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 17th International Conference on E-health Networking, Application & Services (HealthCom)","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/A5048695147","display_name":"Wei-Han Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Wei-Han Chen","raw_affiliation_strings":["Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101673453","display_name":"Hsi\u2010Pin Ma","orcid":"https://orcid.org/0000-0002-0837-4387"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hsi-Pin Ma","raw_affiliation_strings":["Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5048695147"],"corresponding_institution_ids":["https://openalex.org/I25846049"],"apc_list":null,"apc_paid":null,"fwci":1.4728,"has_fulltext":false,"cited_by_count":64,"citation_normalized_percentile":{"value":0.88569897,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.998199999332428,"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":0.998199999332428,"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/T12222","display_name":"IoT-based Smart Home Systems","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9950000047683716,"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/thermopile","display_name":"Thermopile","score":0.8707951307296753},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7113078832626343},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6548876166343689},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6078857183456421},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6057539582252502},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5814592838287354},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5575100779533386},{"id":"https://openalex.org/keywords/infrared","display_name":"Infrared","score":0.528954267501831},{"id":"https://openalex.org/keywords/image-sensor","display_name":"Image sensor","score":0.501868724822998},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.4870817959308624},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4634862244129181},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.4178622364997864},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.417781263589859},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.19004341959953308},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17940682172775269},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.17928513884544373},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.10185346007347107}],"concepts":[{"id":"https://openalex.org/C47279676","wikidata":"https://www.wikidata.org/wiki/Q915693","display_name":"Thermopile","level":3,"score":0.8707951307296753},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7113078832626343},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6548876166343689},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6078857183456421},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6057539582252502},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5814592838287354},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5575100779533386},{"id":"https://openalex.org/C158355884","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Infrared","level":2,"score":0.528954267501831},{"id":"https://openalex.org/C76935873","wikidata":"https://www.wikidata.org/wiki/Q209121","display_name":"Image sensor","level":2,"score":0.501868724822998},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.4870817959308624},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4634862244129181},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.4178622364997864},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.417781263589859},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.19004341959953308},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17940682172775269},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.17928513884544373},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.10185346007347107},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/healthcom.2015.7454538","is_oa":false,"landing_page_url":"https://doi.org/10.1109/healthcom.2015.7454538","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 17th International Conference on E-health Networking, Application & Services (HealthCom)","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":18,"referenced_works":["https://openalex.org/W1986684752","https://openalex.org/W1990214904","https://openalex.org/W1997551825","https://openalex.org/W2005828157","https://openalex.org/W2005864049","https://openalex.org/W2046679149","https://openalex.org/W2064478533","https://openalex.org/W2066109980","https://openalex.org/W2072054122","https://openalex.org/W2090126557","https://openalex.org/W2121292082","https://openalex.org/W2149404071","https://openalex.org/W2154770871","https://openalex.org/W2156915253","https://openalex.org/W2170857713","https://openalex.org/W2541166653","https://openalex.org/W3145740684","https://openalex.org/W6666793874"],"related_works":["https://openalex.org/W1598554143","https://openalex.org/W1497220320","https://openalex.org/W4319301974","https://openalex.org/W4328092585","https://openalex.org/W2895400523","https://openalex.org/W2072051682","https://openalex.org/W1551902208","https://openalex.org/W2139783875","https://openalex.org/W1873415836","https://openalex.org/W4312469487"],"abstract_inverted_index":{"In":[0,203],"this":[1],"paper,":[2],"a":[3,28,135],"low":[4],"resolution":[5],"privacy":[6],"preserved":[7],"infrared":[8,49,56],"array":[9,33],"sensor":[10,24,50,107,175],"is":[11,25,81,108,112,123,144,155,180],"adopted":[12],"for":[13,69,182,199],"the":[14,17,35,52,61,71,85,88,92,97,100,115,126,131,137,148,151,159,162,168,171,183,193,200],"applications":[15],"of":[16,27,41,48,78,102,140],"elderly":[18],"tracking":[19,142],"and":[20,208,219],"fall":[21,152,201,206],"detection.":[22,202],"The":[23,76,110,120,174,187],"composed":[26],"16":[29],"\u00d7":[30,38],"4":[31],"thermopile":[32,46],"with":[34,87,176],"corresponding":[36],"60\u00b0":[37],"16.4\u00b0":[39],"field":[40],"view.":[42],"Each":[43],"pixel":[44],"or":[45],"element":[47],"contains":[51],"temperature":[53,93],"value.":[54],"Two":[55,165],"sensors":[57,166],"are":[58,190,212,222],"attached":[59],"to":[60,125,129,192],"wall":[62],"at":[63,170],"different":[64],"places":[65],"in":[66],"our":[67,141],"system":[68],"capturing":[70],"three":[72],"dimensional":[73],"image":[74,86],"information.":[75],"foreground":[77,98,178],"human":[79],"body":[80],"determined":[82],"by":[83,114,157],"subtracting":[84],"background":[89],"model":[90,128,198],"using":[91],"difference":[94],"characteristic.":[95],"Using":[96],"temperature,":[99],"angle":[101],"arrival":[103],"(AOA)":[104],"from":[105,161],"each":[106],"obtained.":[109],"location":[111],"estimated":[113,121],"AOA":[116],"based":[117],"positioning":[118,132],"algorithm.":[119],"position":[122],"passed":[124],"regression":[127],"reduce":[130],"error.":[133],"As":[134],"result,":[136],"mean":[138],"error":[139],"algorithm":[143,154],"13.39":[145],"cm.":[146],"On":[147],"other":[149],"hand,":[150],"detection":[153],"implemented":[156],"extracting":[158],"features":[160,189],"falling":[163],"action.":[164],"capture":[167],"action":[169],"same":[172],"time.":[173],"larger":[177],"region":[179],"chosen":[181],"feature":[184],"extraction":[185],"process.":[186],"extracted":[188],"applied":[191],"k-nearest":[194],"neighbor":[195],"(k-NN)":[196],"classification":[197],"experiment,":[204],"80":[205,209],"actions":[207,211],"normal":[210],"collected.":[213],"Finally,":[214],"95.25%":[215],"sensitivity,":[216],"90.75%":[217],"specificity":[218],"93%":[220],"accuracy":[221],"achieved.":[223]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}