{"id":"https://openalex.org/W2163535356","doi":"https://doi.org/10.1007/s11042-013-1473-1","title":"Detecting gait-related health problems of the elderly using multidimensional dynamic time warping approach with semantic attributes","display_name":"Detecting gait-related health problems of the elderly using multidimensional dynamic time warping approach with semantic attributes","publication_year":2013,"publication_date":"2013-05-31","ids":{"openalex":"https://openalex.org/W2163535356","doi":"https://doi.org/10.1007/s11042-013-1473-1","mag":"2163535356"},"language":"en","primary_location":{"id":"doi:10.1007/s11042-013-1473-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11042-013-1473-1","pdf_url":null,"source":{"id":"https://openalex.org/S110206669","display_name":"Multimedia Tools and Applications","issn_l":"1380-7501","issn":["1380-7501","1573-7721"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Multimedia Tools and Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1007/s11042-013-1473-1","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041499712","display_name":"Bogdan Pogorelc","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113529","display_name":"Jo\u017eef Stefan International Postgraduate School","ror":"https://ror.org/01hdkb925","country_code":"SI","type":"education","lineage":["https://openalex.org/I4210113529"]},{"id":"https://openalex.org/I3006985408","display_name":"Jo\u017eef Stefan Institute","ror":"https://ror.org/05060sz93","country_code":"SI","type":"facility","lineage":["https://openalex.org/I3006985408"]},{"id":"https://openalex.org/I4210103955","display_name":"Spica International (Slovenia)","ror":"https://ror.org/01f3xmn08","country_code":"SI","type":"company","lineage":["https://openalex.org/I4210103955"]}],"countries":["SI"],"is_corresponding":true,"raw_author_name":"Bogdan Pogorelc","raw_affiliation_strings":["Jozef Stefan International Postgraduate School, Jamova 39, 1000, Ljubljana, Slovenia","Jo\u017eef Stefan Institute, Department of Intelligent Systems, Jamova c. 39, 1000, Ljubljana, Slovenia","\u0160pica International d. o. o., Pot k sejmi\u0161\u010du 33, 1231, Ljubljana, Slovenia"],"affiliations":[{"raw_affiliation_string":"Jozef Stefan International Postgraduate School, Jamova 39, 1000, Ljubljana, Slovenia","institution_ids":["https://openalex.org/I4210113529"]},{"raw_affiliation_string":"Jo\u017eef Stefan Institute, Department of Intelligent Systems, Jamova c. 39, 1000, Ljubljana, Slovenia","institution_ids":["https://openalex.org/I3006985408"]},{"raw_affiliation_string":"\u0160pica International d. o. o., Pot k sejmi\u0161\u010du 33, 1231, Ljubljana, Slovenia","institution_ids":["https://openalex.org/I4210103955"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043419128","display_name":"Matja\u017e Gams","orcid":"https://orcid.org/0000-0002-5747-0711"},"institutions":[{"id":"https://openalex.org/I3006985408","display_name":"Jo\u017eef Stefan Institute","ror":"https://ror.org/05060sz93","country_code":"SI","type":"facility","lineage":["https://openalex.org/I3006985408"]},{"id":"https://openalex.org/I4210113529","display_name":"Jo\u017eef Stefan International Postgraduate School","ror":"https://ror.org/01hdkb925","country_code":"SI","type":"education","lineage":["https://openalex.org/I4210113529"]},{"id":"https://openalex.org/I4210103955","display_name":"Spica International (Slovenia)","ror":"https://ror.org/01f3xmn08","country_code":"SI","type":"company","lineage":["https://openalex.org/I4210103955"]}],"countries":["SI"],"is_corresponding":false,"raw_author_name":"Matja\u017e Gams","raw_affiliation_strings":["Jozef Stefan International Postgraduate School, Jamova 39, 1000, Ljubljana, Slovenia","Jo\u017eef Stefan Institute, Department of Intelligent Systems, Jamova c. 39, 1000, Ljubljana, Slovenia","\u0160pica International d. o. o., Pot k sejmi\u0161\u010du 33, 1231, Ljubljana, Slovenia"],"affiliations":[{"raw_affiliation_string":"Jozef Stefan International Postgraduate School, Jamova 39, 1000, Ljubljana, Slovenia","institution_ids":["https://openalex.org/I4210113529"]},{"raw_affiliation_string":"Jo\u017eef Stefan Institute, Department of Intelligent Systems, Jamova c. 39, 1000, Ljubljana, Slovenia","institution_ids":["https://openalex.org/I3006985408"]},{"raw_affiliation_string":"\u0160pica International d. o. o., Pot k sejmi\u0161\u010du 33, 1231, Ljubljana, Slovenia","institution_ids":["https://openalex.org/I4210103955"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5041499712"],"corresponding_institution_ids":["https://openalex.org/I3006985408","https://openalex.org/I4210103955","https://openalex.org/I4210113529"],"apc_list":null,"apc_paid":null,"fwci":1.9292,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.87194419,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"66","issue":"1","first_page":"95","last_page":"114"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9861999750137329,"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/dynamic-time-warping","display_name":"Dynamic time warping","score":0.8824598789215088},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8473565578460693},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.604678213596344},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5756669640541077},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5280103087425232},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39908161759376526},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3901161551475525},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33761847019195557}],"concepts":[{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.8824598789215088},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8473565578460693},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.604678213596344},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5756669640541077},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5280103087425232},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39908161759376526},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3901161551475525},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33761847019195557},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11042-013-1473-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11042-013-1473-1","pdf_url":null,"source":{"id":"https://openalex.org/S110206669","display_name":"Multimedia Tools and Applications","issn_l":"1380-7501","issn":["1380-7501","1573-7721"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Multimedia Tools and Applications","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11042-013-1473-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11042-013-1473-1","pdf_url":null,"source":{"id":"https://openalex.org/S110206669","display_name":"Multimedia Tools and Applications","issn_l":"1380-7501","issn":["1380-7501","1573-7721"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Multimedia Tools and Applications","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320338080","display_name":"European Social Fund","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W8722571","https://openalex.org/W121610656","https://openalex.org/W1689099703","https://openalex.org/W1767943021","https://openalex.org/W1853465296","https://openalex.org/W1881680478","https://openalex.org/W1915297548","https://openalex.org/W1961033081","https://openalex.org/W1984860717","https://openalex.org/W2010961767","https://openalex.org/W2021761995","https://openalex.org/W2067342415","https://openalex.org/W2081241079","https://openalex.org/W2081924655","https://openalex.org/W2086137009","https://openalex.org/W2091921805","https://openalex.org/W2116341417","https://openalex.org/W2123847366","https://openalex.org/W2128160875","https://openalex.org/W2137089646","https://openalex.org/W2144994235","https://openalex.org/W2149350027","https://openalex.org/W2166630128","https://openalex.org/W2434988359","https://openalex.org/W2970715575","https://openalex.org/W3149365120","https://openalex.org/W4205431832"],"related_works":["https://openalex.org/W2030799363","https://openalex.org/W2950183183","https://openalex.org/W2341338763","https://openalex.org/W2032415964","https://openalex.org/W2288425735","https://openalex.org/W2349923317","https://openalex.org/W2894081631","https://openalex.org/W2986063033","https://openalex.org/W2040439981","https://openalex.org/W2472888994"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,39,222],"health-monitoring":[3],"system":[4,41],"based":[5],"on":[6,169],"the":[7,17,23,33,62,67,75,116,140,143,149,158,161,167,170,183,204,214,243,272],"multidimensional":[8,150],"dynamic":[9,122],"time":[10,59,151,171],"warping":[11],"approach":[12,70,124,245],"with":[13,38,66,125,148,153,208],"semantic":[14,126,154,177],"attributes":[15,178,212],"for":[16],"detection":[18],"of":[19,32,44,61,79,88,100,106,115,142,160,173,182,193,227,257,268],"health":[20,77,101,196,234,260],"problems":[21],"in":[22,54,71,135,201],"elderly":[24,34,81,107,229],"to":[25,73,98,146,189,203,253,271],"prolong":[26],"their":[27,109],"autonomous":[28],"living.":[29],"The":[30,57,112,176,216],"movement":[31,226],"user":[35],"is":[36,85,119,130,139,246],"captured":[37],"motion-capture":[40],"that":[42,186],"consists":[43],"body-worn":[45],"tags,":[46],"whose":[47,128],"coordinates":[48,63],"are":[49,64,187],"acquired":[50],"by":[51],"sensors":[52],"located":[53],"an":[55,80,86,228],"apartment.":[56],"output":[58],"series":[60,152,172],"modeled":[65],"proposed":[68,93],"data-mining":[69],"order":[72],"recognize":[74,190],"specific":[76,206,209,274],"problem":[78],"person.":[82],"This":[83],"paper":[84],"extension":[87],"our":[89],"previous":[90],"study,":[91],"which":[92],"four":[94,117,239],"data":[95],"mining":[96],"approaches":[97,118,207],"recognition":[99],"problems,":[102,197,261],"falls":[103,198],"and":[104,132,199,238,249],"activities":[105,258],"from":[108,213],"motion":[110],"patterns.":[111],"most":[113],"successful":[114],"SMDTW":[120,138,162,220],"(Multidimensional":[121],"time-warping":[123],"attributes),":[127],"version":[129],"used":[131,252],"thoroughly":[133],"analyzed":[134],"this":[136,164],"paper.":[137],"modification":[141],"DTW":[144,168],"algorithm":[145],"use":[147],"attributes.":[155],"To":[156],"test":[157],"robustness":[159],"approach,":[163],"study":[165],"calculates":[166],"various":[174],"lengths.":[175],"presented":[179],"here":[180],"consist":[181],"joint":[184],"angles":[185],"able":[188],"many":[191],"types":[192,256],"movement,":[194],"e.g.,":[195],"activities,":[200],"contrast":[202],"more":[205,247,273],"medically":[210],"defined":[211],"literature.":[215],"k-nearest-neighbor":[217],"classifier":[218],"using":[219],"as":[221],"distance":[223],"measure":[224],"classifies":[225],"person":[230],"into":[231],"five":[232],"different":[233],"states:":[235],"one":[236],"healthy":[237],"unhealthy.":[240],"Even":[241],"though":[242],"new":[244],"general":[248],"can":[250],"be":[251],"differentiate":[254],"other":[255],"or":[259],"it":[262],"achieves":[263],"very":[264],"high":[265],"classification":[266],"accuracy":[267],"97.2%,":[269],"comparable":[270],"approaches.":[275]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}
