{"id":"https://openalex.org/W3034259607","doi":"https://doi.org/10.1109/cbs46900.2019.9114487","title":"Elderly Fall Risk Prediction with Plantar Center of Force Using ConvLSTM Algorithm","display_name":"Elderly Fall Risk Prediction with Plantar Center of Force Using ConvLSTM Algorithm","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W3034259607","doi":"https://doi.org/10.1109/cbs46900.2019.9114487","mag":"3034259607"},"language":"en","primary_location":{"id":"doi:10.1109/cbs46900.2019.9114487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cbs46900.2019.9114487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Cyborg and Bionic Systems (CBS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5074307825","display_name":"Shengyun Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengyun Liang","raw_affiliation_strings":["CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,Shenzhen,China","CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,Shenzhen,China","institution_ids":["https://openalex.org/I4210145761"]},{"raw_affiliation_string":"CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101533871","display_name":"Yimeng Liu","orcid":"https://orcid.org/0000-0002-6742-2908"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yimeng Liu","raw_affiliation_strings":["CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,Shenzhen,China","CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,Shenzhen,China","institution_ids":["https://openalex.org/I4210145761"]},{"raw_affiliation_string":"CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100636088","display_name":"Guanglin Li","orcid":"https://orcid.org/0000-0001-9016-2617"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanglin Li","raw_affiliation_strings":["CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,Shenzhen,China","CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,Shenzhen,China","institution_ids":["https://openalex.org/I4210145761"]},{"raw_affiliation_string":"CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040518468","display_name":"Guoru Zhao","orcid":"https://orcid.org/0000-0001-9348-9236"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoru Zhao","raw_affiliation_strings":["CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,Shenzhen,China","CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,Shenzhen,China","institution_ids":["https://openalex.org/I4210145761"]},{"raw_affiliation_string":"CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"36","last_page":"41"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10114","display_name":"Balance, Gait, and Falls Prevention","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10114","display_name":"Balance, Gait, and Falls Prevention","score":0.9994000196456909,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.993399977684021,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9927999973297119,"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/machine-learning","display_name":"Machine learning","score":0.580315113067627},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5776644945144653},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5589601993560791},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.4631684720516205},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.35751014947891235},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2211339771747589}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.580315113067627},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5776644945144653},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5589601993560791},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.4631684720516205},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.35751014947891235},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2211339771747589}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cbs46900.2019.9114487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cbs46900.2019.9114487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Cyborg and Bionic Systems (CBS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W113447013","https://openalex.org/W1485009520","https://openalex.org/W1550534467","https://openalex.org/W1974704788","https://openalex.org/W2008348094","https://openalex.org/W2008565040","https://openalex.org/W2015679849","https://openalex.org/W2054780155","https://openalex.org/W2062248054","https://openalex.org/W2092280349","https://openalex.org/W2116516133","https://openalex.org/W2132677633","https://openalex.org/W2154446525","https://openalex.org/W2160963242","https://openalex.org/W2172374880","https://openalex.org/W2252628305","https://openalex.org/W2295972917","https://openalex.org/W2540981238","https://openalex.org/W2578674042","https://openalex.org/W2620071263","https://openalex.org/W2766476110","https://openalex.org/W2804907753","https://openalex.org/W3125944242","https://openalex.org/W4294577070","https://openalex.org/W6628877408"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Elderly":[0],"people":[1,81],"are":[2,160],"vulnerable":[3],"to":[4,7,67,100,122,140],"falls":[5,184],"due":[6],"the":[8,28,105,124,127,135,150,157,169,181,186],"decline":[9],"of":[10,104,137,156,175,183],"balance":[11],"ability,":[12],"resulting":[13],"in":[14,27,185],"physical":[15],"injury,":[16],"so":[17],"early":[18,191],"detection":[19],"is":[20,47],"essential":[21],"for":[22,51,89,194],"fall":[23,38,69,195],"prevention":[24],"and":[25,84,115,154,164],"reduction":[26],"elderly.":[29],"Biomechanical":[30],"sensor":[31],"data":[32,103],"can":[33,178],"provide":[34],"valuable":[35],"insight":[36],"into":[37],"risk.":[39],"However,":[40],"extracting":[41],"features":[42],"from":[43],"raw":[44,75],"time":[45],"series":[46],"a":[48,141],"tough":[49],"task":[50],"traditional":[52],"machine":[53],"learning":[54],"methods.":[55],"In":[56],"this":[57,90,176],"paper,":[58],"an":[59,190],"end-to-end":[60],"trainable":[61],"model":[62,139,143,159,177],"named":[63],"ConvLSTM":[64,138,158],"was":[65,98],"proposed":[66],"assess":[68,180],"risk,":[70],"which":[71,167],"works":[72],"directly":[73],"on":[74],"plantar":[76,107],"force":[77,102],"data.":[78],"85":[79],"elderly":[80],"(46":[82],"High-risk":[83],"39":[85],"low-risk)":[86],"were":[87],"recruited":[88],"study.":[91],"A":[92],"Footscan":[93],"<sup":[94],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[95],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">\u00ae</sup>":[96],"system":[97],"used":[99],"collect":[101],"whole":[106],"area":[108],"when":[109],"each":[110],"subject":[111],"walked":[112],"at":[113],"normal":[114],"steady":[116],"speed.":[117],"Firstly,":[118],"we":[119,133],"use":[120],"t-test":[121],"verify":[123],"differences":[125],"between":[126],"two":[128],"risk":[129,182],"groups.":[130],"And":[131],"then":[132],"compared":[134],"performance":[136],"baseline":[142],"called":[144],"DTW-KNN.":[145],"Experimental":[146],"results":[147],"show":[148],"that":[149],"classification":[151],"sensitivity,":[152],"specificity":[153],"accuracy":[155],"optimally":[161],"93%,":[162],"94%":[163,165],"respectively,":[166],"outperforms":[168],"DTW-KNN":[170],"model.":[171],"The":[172],"successful":[173],"application":[174],"accurately":[179],"elderly,":[187],"thus":[188],"providing":[189],"warning":[192],"basis":[193],"intervention.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
