{"id":"https://openalex.org/W2511127197","doi":"https://doi.org/10.1109/memea.2016.7533763","title":"A comparison between heuristic and machine learning techniques in fall detection using Kinect v2","display_name":"A comparison between heuristic and machine learning techniques in fall detection using Kinect v2","publication_year":2016,"publication_date":"2016-05-01","ids":{"openalex":"https://openalex.org/W2511127197","doi":"https://doi.org/10.1109/memea.2016.7533763","mag":"2511127197"},"language":"en","primary_location":{"id":"doi:10.1109/memea.2016.7533763","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea.2016.7533763","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://bura.brunel.ac.uk/bitstream/2438/13290/3/Fulltext.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056172691","display_name":"Amin Amini","orcid":"https://orcid.org/0000-0001-7081-2440"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Amin Amini","raw_affiliation_strings":["Department of Electronics and Computer Engineering, Brunel University London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Computer Engineering, Brunel University London, London, UK","institution_ids":["https://openalex.org/I59433898"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022422624","display_name":"Konstantinos Banitsas","orcid":"https://orcid.org/0000-0003-2658-3032"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Konstantinos Banitsas","raw_affiliation_strings":["Department of Electronics and Computer Engineering, Brunel University London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Computer Engineering, Brunel University London, London, UK","institution_ids":["https://openalex.org/I59433898"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072900428","display_name":"John Cosmas","orcid":"https://orcid.org/0000-0003-4378-5576"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"John Cosmas","raw_affiliation_strings":["Department of Electronics and Computer Engineering, Brunel University London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Computer Engineering, Brunel University London, London, UK","institution_ids":["https://openalex.org/I59433898"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5211,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.8837217,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9994999766349792,"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":0.9994999766349792,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9887999892234802,"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":0.9873999953269958,"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/computer-science","display_name":"Computer science","score":0.7912845015525818},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6896051168441772},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.68928062915802},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.6757420301437378},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5686513781547546},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.45457857847213745},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4420159161090851},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3295760750770569}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7912845015525818},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6896051168441772},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.68928062915802},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.6757420301437378},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5686513781547546},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.45457857847213745},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4420159161090851},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3295760750770569},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/memea.2016.7533763","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea.2016.7533763","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","raw_type":"proceedings-article"},{"id":"pmh:oai:bura.brunel.ac.uk:2438/13290","is_oa":true,"landing_page_url":"http://bura.brunel.ac.uk/handle/2438/13290","pdf_url":"http://bura.brunel.ac.uk/bitstream/2438/13290/3/Fulltext.pdf","source":{"id":"https://openalex.org/S4306401473","display_name":"Brunel University Research Archive (BURA) (Brunel University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59433898","host_organization_name":"Brunel University of London","host_organization_lineage":["https://openalex.org/I59433898"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":{"id":"pmh:oai:bura.brunel.ac.uk:2438/13290","is_oa":true,"landing_page_url":"http://bura.brunel.ac.uk/handle/2438/13290","pdf_url":"http://bura.brunel.ac.uk/bitstream/2438/13290/3/Fulltext.pdf","source":{"id":"https://openalex.org/S4306401473","display_name":"Brunel University Research Archive (BURA) (Brunel University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59433898","host_organization_name":"Brunel University of London","host_organization_lineage":["https://openalex.org/I59433898"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"},"sustainable_development_goals":[{"score":0.44999998807907104,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W2511127197.pdf"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W1643469768","https://openalex.org/W1975130119","https://openalex.org/W2043495858","https://openalex.org/W2059584741","https://openalex.org/W2100716893","https://openalex.org/W2104619880","https://openalex.org/W2114933419","https://openalex.org/W2145039676","https://openalex.org/W2146855205","https://openalex.org/W2317053768","https://openalex.org/W2319308093"],"related_works":["https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W1549363203","https://openalex.org/W4231274751","https://openalex.org/W2154063878","https://openalex.org/W2556012038","https://openalex.org/W1489772951","https://openalex.org/W3082059448","https://openalex.org/W4313640622","https://openalex.org/W1828750805"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"two":[3,96],"algorithms":[4],"were":[5],"tested":[6],"on":[7,13,18,45,82],"11":[8],"healthy":[9],"adults:":[10],"one":[11,17,99,108,124],"based":[12,44],"heuristic":[14,35,140,152],"and":[15,50,89,107,142],"another":[16,125],"video":[19,71],"tagging":[20,72],"machine":[21,56,146,181],"learning":[22,57,147,182],"methods":[23],"for":[24,157,179],"automatic":[25],"fall":[26,75,93,158],"detection;":[27],"both":[28],"utilizing":[29,63],"Microsoft":[30],"Kinect":[31],"v2.":[32],"For":[33,54,77],"our":[34],"approach,":[36,58,79],"we":[37,59],"used":[38],"skeletal":[39],"data":[40],"to":[41,73],"detect":[42],"falls":[43],"a":[46,61,163,180],"set":[47],"of":[48,113,117,134,166],"instructions":[49],"signal":[51],"filtering":[52],"methods.":[53],"the":[55,64,104,139,172,177],"implemented":[60],"dataset":[62,168],"Adaptive":[65],"Boosting":[66],"Trigger":[67],"(AdaBoostTrigger)":[68],"algorithm":[69],"via":[70],"enable":[74],"detection.":[76],"each":[78,80,118],"subject":[81],"average":[83,133],"has":[84,120],"performed":[85],"six":[86,90],"true":[87],"positive":[88,92],"false":[91],"incidents":[94],"in":[95,126,138,145],"different":[97,127],"conditions:":[98],"with":[100,109],"objects":[101],"partially":[102],"blocking":[103],"sensor's":[105],"view":[106],"partial":[110],"obstructed":[111],"field":[112],"view.":[114],"The":[115,129],"accuracy":[116,137],"approach":[119,141,153],"been":[121],"compared":[122],"against":[123],"conditions.":[128],"result":[130],"showed":[131],"an":[132],"95.42":[135],"%":[136,144],"88.33":[143],"technique.":[148],"We":[149],"conclude":[150],"that":[151],"performs":[154],"more":[155],"accurately":[156],"detection":[159],"when":[160],"there":[161],"is":[162,184],"limited":[164],"number":[165],"training":[167],"available.":[169],"Nevertheless,":[170],"as":[171],"gesture":[173],"detection's":[174],"complexity":[175],"increases,":[176],"need":[178],"technique":[183],"inevitable.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}