{"id":"https://openalex.org/W2950232456","doi":"https://doi.org/10.1109/access.2019.2923077","title":"Automatic Detection of Compensatory Movement Patterns by a Pressure Distribution Mattress Using Machine Learning Methods: A Pilot Study","display_name":"Automatic Detection of Compensatory Movement Patterns by a Pressure Distribution Mattress Using Machine Learning Methods: A Pilot Study","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2950232456","doi":"https://doi.org/10.1109/access.2019.2923077","mag":"2950232456"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2923077","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2923077","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08736746.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08736746.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088380372","display_name":"Siqi Cai","orcid":"https://orcid.org/0000-0003-3282-9246"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siqi Cai","raw_affiliation_strings":["Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-3282-9246","affiliations":[{"raw_affiliation_string":"Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100342225","display_name":"Guofeng Li","orcid":"https://orcid.org/0000-0002-2271-6283"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guofeng Li","raw_affiliation_strings":["Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081081770","display_name":"Shuangyuan Huang","orcid":"https://orcid.org/0000-0002-4258-8311"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuangyuan Huang","raw_affiliation_strings":["Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4258-8311","affiliations":[{"raw_affiliation_string":"Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100666268","display_name":"Haiqing Zheng","orcid":"https://orcid.org/0000-0001-7385-3037"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210146956","display_name":"Third Affiliated Hospital of Sun Yat-sen University","ror":"https://ror.org/04tm3k558","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210146956"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiqing Zheng","raw_affiliation_strings":["Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I4210146956","https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025392221","display_name":"Longhan Xie","orcid":"https://orcid.org/0000-0002-5137-1413"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Longhan Xie","raw_affiliation_strings":["Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.1186,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.82129529,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"7","issue":null,"first_page":"80300","last_page":"80309"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.991599977016449,"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":0.991599977016449,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9911999702453613,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9822999835014343,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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":0.6436359882354736},{"id":"https://openalex.org/keywords/movement","display_name":"Movement (music)","score":0.5491983890533447},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43739986419677734},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3751031756401062},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.10068434476852417}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6436359882354736},{"id":"https://openalex.org/C2780226923","wikidata":"https://www.wikidata.org/wiki/Q929848","display_name":"Movement (music)","level":2,"score":0.5491983890533447},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43739986419677734},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3751031756401062},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.10068434476852417},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2923077","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2923077","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08736746.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3b813bce287045d8bd4c49e8048b010d","is_oa":true,"landing_page_url":"https://doaj.org/article/3b813bce287045d8bd4c49e8048b010d","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 80300-80309 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2923077","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2923077","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08736746.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7859882191","display_name":null,"funder_award_id":"51575188","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2950232456.pdf","grobid_xml":"https://content.openalex.org/works/W2950232456.grobid-xml"},"referenced_works_count":58,"referenced_works":["https://openalex.org/W1660633054","https://openalex.org/W1680392829","https://openalex.org/W1809259931","https://openalex.org/W1817561967","https://openalex.org/W1970191726","https://openalex.org/W1974727501","https://openalex.org/W1993331944","https://openalex.org/W1997754031","https://openalex.org/W2015228557","https://openalex.org/W2032323291","https://openalex.org/W2032481801","https://openalex.org/W2039539255","https://openalex.org/W2050597795","https://openalex.org/W2051123042","https://openalex.org/W2051462644","https://openalex.org/W2053456037","https://openalex.org/W2057187202","https://openalex.org/W2062929572","https://openalex.org/W2065684189","https://openalex.org/W2066005892","https://openalex.org/W2084500901","https://openalex.org/W2089282851","https://openalex.org/W2106975581","https://openalex.org/W2110367281","https://openalex.org/W2111774890","https://openalex.org/W2142505388","https://openalex.org/W2146504676","https://openalex.org/W2147376995","https://openalex.org/W2160638979","https://openalex.org/W2165193162","https://openalex.org/W2170505850","https://openalex.org/W2278557308","https://openalex.org/W2402297854","https://openalex.org/W2442464620","https://openalex.org/W2591746674","https://openalex.org/W2593493570","https://openalex.org/W2600153465","https://openalex.org/W2604870469","https://openalex.org/W2608457541","https://openalex.org/W2611471088","https://openalex.org/W2616795627","https://openalex.org/W2706802801","https://openalex.org/W2743927120","https://openalex.org/W2762856607","https://openalex.org/W2766557230","https://openalex.org/W2767166049","https://openalex.org/W2773114850","https://openalex.org/W2782922652","https://openalex.org/W2783290178","https://openalex.org/W2807319534","https://openalex.org/W2921192162","https://openalex.org/W4236110830","https://openalex.org/W4293875374","https://openalex.org/W6637386731","https://openalex.org/W6677182444","https://openalex.org/W6718017340","https://openalex.org/W6737636857","https://openalex.org/W6745051936"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347","https://openalex.org/W4210805261"],"abstract_inverted_index":{"For":[0,233],"stroke":[1,294],"patients":[2],"with":[3,6,13,111],"hemiplegia,":[4],"reaching":[5,117,231],"the":[7,45,49,159,168,176,184,234,241,291,298],"paretic":[8,50],"arm":[9,20],"is":[10,41,86,90,102],"often":[11],"associated":[12],"compensatory":[14,30,53,76,130,198,238,283],"movements":[15],"due":[16],"to":[17,94,150,172,180,196,289,296],"limited":[18],"active":[19],"movement":[21,31,54,77,131,199,239,284],"and":[22,38,61,68,97,105,121,128,135,137,148,175,201,205,211,260,266,300],"a":[23,75,82,91,125,152,245,277],"loss":[24],"of":[25,48,143,154,162,166,170,178,186,237,276],"interjoint":[26],"coordination.":[27],"Detecting":[28],"common":[29],"patterns,":[32,240],"such":[33],"as":[34],"excessive":[35],"trunk":[36,250,261],"displacement":[37],"scapular":[39,138,255],"elevation,":[40],"critical":[42],"for":[43,249,281],"improving":[44],"motor":[46,113],"function":[47],"arm.":[51],"Existing":[52],"pattern":[55,78,127],"detection":[56,79],"methods,":[57],"including":[58],"sensor-based":[59],"systems":[60],"camera-based":[62],"systems,":[63],"suffer":[64],"from":[65],"object":[66],"obstruction":[67],"require":[69],"complex":[70],"setups.":[71],"In":[72],"this":[73],"paper,":[74],"system":[80],"using":[81],"pressure":[83,278],"distribution":[84,141,279],"mattress":[85,280],"presented.":[87],"This":[88],"method":[89],"novel":[92],"approach":[93,292],"detect":[95,197],"compensations":[96],"has":[98],"observed":[99],"advantages;":[100],"it":[101],"simple,":[103],"unobtrusive":[104],"low":[106],"cost.":[107],"Fifteen":[108],"healthy":[109],"participants":[110],"no":[112],"impairments":[114],"performed":[115],"three":[116],"tasks":[118],"(back-and-forth,":[119],"side-to-side,":[120],"up-and-down":[122],"reaching)":[123],"in":[124,129,226],"normal":[126],"patterns":[132,200],"(trunk":[133],"rotation":[134,262],"lean-forward,":[136],"elevation).":[139],"Pressure":[140],"data":[142],"all":[144,230],"motions":[145],"were":[146,194],"recorded":[147],"processed":[149],"generate":[151],"group":[153],"features":[155],"(average":[156],"sensor":[157],"values,":[158],"lateral":[160],"center":[161,165],"pressure,":[163,167,174],"longitudinal":[164],"ratio":[169,177],"left-side":[171],"right-side":[173],"front-side":[179],"back-side":[181],"pressure)":[182],"reflecting":[183],"information":[185],"each":[187],"predefined":[188],"pattern.":[189],"Four":[190],"machine":[191,214],"learning":[192],"methods":[193],"implemented":[195],"showed":[202],"good":[203,246],"reliability":[204],"precision.":[206],"Both":[207],"k-nearest":[208],"neighbor":[209],"(kNN)":[210],"support":[212],"vector":[213],"(SVM)":[215],"classifiers":[216],"have":[217],"achieved":[218],"an":[219],"excellent":[220],"classification":[221,236,247],"performance":[222,248],"(F1-score":[223,252,257,263],"=":[224,253,258,264],"0.934)":[225],"detecting":[227,282],"compensation":[228],"during":[229],"tasks.":[232],"multiclass":[235],"SVM":[242],"classifier":[243],"exhibited":[244],"lean-forward":[251],"0.933),":[254],"elevation":[256],"0.881),":[259],"0.854)":[265],"outperformed":[267],"previous":[268],"reports.":[269],"The":[270],"study":[271],"results":[272],"provide":[273],"initial":[274],"evidence":[275],"patterns.":[285],"Future":[286],"work":[287],"needs":[288],"test":[290],"on":[293],"survivors":[295],"verified":[297],"feasibility":[299],"validity.":[301]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}