{"id":"https://openalex.org/W4391093462","doi":"https://doi.org/10.1109/iciscae59047.2023.10393357","title":"A LSTM-ANN Model for the Prediction of Hip Flexion and Extension Moment at the Next Time","display_name":"A LSTM-ANN Model for the Prediction of Hip Flexion and Extension Moment at the Next Time","publication_year":2023,"publication_date":"2023-09-23","ids":{"openalex":"https://openalex.org/W4391093462","doi":"https://doi.org/10.1109/iciscae59047.2023.10393357"},"language":"en","primary_location":{"id":"doi:10.1109/iciscae59047.2023.10393357","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iciscae59047.2023.10393357","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 6th International Conference on Information Systems and Computer Aided Education (ICISCAE)","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/A5012799900","display_name":"Hui Zeng","orcid":"https://orcid.org/0000-0001-6862-6964"},"institutions":[{"id":"https://openalex.org/I83791580","display_name":"Fujian University of Technology","ror":"https://ror.org/03c8fdb16","country_code":"CN","type":"education","lineage":["https://openalex.org/I83791580"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hui Zeng","raw_affiliation_strings":["Fujian University of Technology,Fuzhou,China","Fujian University of Technology, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"Fujian University of Technology,Fuzhou,China","institution_ids":["https://openalex.org/I83791580"]},{"raw_affiliation_string":"Fujian University of Technology, Fuzhou, China","institution_ids":["https://openalex.org/I83791580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100447333","display_name":"Ming Zhang","orcid":"https://orcid.org/0000-0003-3827-8801"},"institutions":[{"id":"https://openalex.org/I83791580","display_name":"Fujian University of Technology","ror":"https://ror.org/03c8fdb16","country_code":"CN","type":"education","lineage":["https://openalex.org/I83791580"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Zhang","raw_affiliation_strings":["Fujian University of Technology,Fuzhou,China","Fujian University of Technology, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"Fujian University of Technology,Fuzhou,China","institution_ids":["https://openalex.org/I83791580"]},{"raw_affiliation_string":"Fujian University of Technology, Fuzhou, China","institution_ids":["https://openalex.org/I83791580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053586802","display_name":"Yixiang Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I2800350601","display_name":"Central Committee of the Communist Party of China","ror":"https://ror.org/00akhyy70","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800350601"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixiang Zeng","raw_affiliation_strings":["Municipal Committee of the Communist Party of China,Party School of Zigong,Zigong,China","Party School of Zigong, Municipal Committee of the Communist Party of China, Zigong, China"],"affiliations":[{"raw_affiliation_string":"Municipal Committee of the Communist Party of China,Party School of Zigong,Zigong,China","institution_ids":["https://openalex.org/I2800350601"]},{"raw_affiliation_string":"Party School of Zigong, Municipal Committee of the Communist Party of China, Zigong, China","institution_ids":["https://openalex.org/I2800350601"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049784866","display_name":"Dequ Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I83791580","display_name":"Fujian University of Technology","ror":"https://ror.org/03c8fdb16","country_code":"CN","type":"education","lineage":["https://openalex.org/I83791580"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dequ Chen","raw_affiliation_strings":["Fujian University of Technology,Fuzhou,China","Fujian University of Technology, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"Fujian University of Technology,Fuzhou,China","institution_ids":["https://openalex.org/I83791580"]},{"raw_affiliation_string":"Fujian University of Technology, Fuzhou, China","institution_ids":["https://openalex.org/I83791580"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5012799900"],"corresponding_institution_ids":["https://openalex.org/I83791580"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18547019,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"310","last_page":"313"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9997000098228455,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10510","display_name":"Stroke Rehabilitation and Recovery","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/2742","display_name":"Rehabilitation"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/moment","display_name":"Moment (physics)","score":0.837424635887146},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.668269157409668},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5631900429725647},{"id":"https://openalex.org/keywords/current","display_name":"Current (fluid)","score":0.4919118881225586},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47031155228614807},{"id":"https://openalex.org/keywords/treadmill","display_name":"Treadmill","score":0.4394795298576355},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43036219477653503},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32892972230911255},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16962796449661255},{"id":"https://openalex.org/keywords/physical-therapy","display_name":"Physical therapy","score":0.16670864820480347},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.14615479111671448},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.09531739354133606},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07101595401763916}],"concepts":[{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.837424635887146},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.668269157409668},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5631900429725647},{"id":"https://openalex.org/C148043351","wikidata":"https://www.wikidata.org/wiki/Q4456944","display_name":"Current (fluid)","level":2,"score":0.4919118881225586},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47031155228614807},{"id":"https://openalex.org/C2781464450","wikidata":"https://www.wikidata.org/wiki/Q839144","display_name":"Treadmill","level":2,"score":0.4394795298576355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43036219477653503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32892972230911255},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16962796449661255},{"id":"https://openalex.org/C1862650","wikidata":"https://www.wikidata.org/wiki/Q186005","display_name":"Physical therapy","level":1,"score":0.16670864820480347},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.14615479111671448},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.09531739354133606},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07101595401763916},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iciscae59047.2023.10393357","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iciscae59047.2023.10393357","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 6th International Conference on Information Systems and Computer Aided Education (ICISCAE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W116358897","https://openalex.org/W1547359247","https://openalex.org/W2084067034","https://openalex.org/W2087357071","https://openalex.org/W2098283624","https://openalex.org/W2132241160","https://openalex.org/W2535588239","https://openalex.org/W2754242197","https://openalex.org/W2784306847","https://openalex.org/W2811395591","https://openalex.org/W2964804232","https://openalex.org/W2979728443","https://openalex.org/W2987704671","https://openalex.org/W2991349274","https://openalex.org/W3016053754","https://openalex.org/W3090823262","https://openalex.org/W3126964215","https://openalex.org/W3130807160"],"related_works":["https://openalex.org/W1996130883","https://openalex.org/W2748574964","https://openalex.org/W1982412832","https://openalex.org/W2888483922","https://openalex.org/W4244464241","https://openalex.org/W4396737233","https://openalex.org/W2384573129","https://openalex.org/W2351224547","https://openalex.org/W2358945257","https://openalex.org/W4318692582"],"abstract_inverted_index":{"Human":[0],"joint":[1,19,35,69,88,99,108,123,189,201,225],"moment":[2,20,70,100,109,147,164,190,195],"are":[3],"usually":[4],"used":[5],"in":[6,40,63],"rehabilitation":[7,11,219],"equipment,":[8],"the":[9,16,24,32,68,73,84,106,113,117,122,150,163,176,180,185,188,193,197,204,223],"current":[10,18,118,151,181,205],"training":[12],"aids":[13],"rely":[14],"on":[15,57,137],"patient's":[17,25,33],"data":[21,71,131],"to":[22,66,96,221],"determine":[23],"action,":[26],"and":[27,76,87,121,156,200,212],"lack":[28],"of":[29,31,72,116,146],"prediction":[30,101,148,165,177,210],"subsequent":[34],"moment,":[36,206],"which":[37,170,207],"is":[38,61,154,157,171],"inconvenient":[39],"real":[41],"life.":[42],"To":[43],"address":[44],"this":[45,64],"problem,":[46],"a":[47,79,91,138,141,167,214],"new":[48],"fully":[49],"connected":[50],"artificial":[51],"neural":[52],"network":[53],"model":[54,104,127],"(LSTM-ANN)":[55],"based":[56],"capturing":[58,112],"remote":[59,114],"dependencies":[60],"investigated":[62],"paper":[65],"predict":[67,222],"hip":[74],"flexion":[75],"extension":[77],"after":[78,90,166],"given":[80,92,168],"time":[81,152],"by":[82,111],"predicting":[83],"electromyogram":[85,119],"signals":[86],"angles":[89],"time.":[93],"In":[94,183],"contrast":[95],"existing":[97],"human":[98,224],"models,":[102],"our":[103],"predicts":[105,187],"next":[107,194],"values":[110],"dependence":[115],"signal":[120,199],"angle.":[124],"The":[125,144],"LSTM-ANN":[126],"was":[128],"validated":[129],"using":[130],"from":[132,175,196],"six":[133],"healthy":[134],"subjects":[135],"exercising":[136],"treadmill":[139],"at":[140,149,179,192,203],"constant":[142],"speed.":[143],"accuracy":[145,211],"period":[153],"95.38%":[155],"as":[158,160],"high":[159],"93.58%":[161],"for":[162,217],"time,":[169],"not":[172],"much":[173],"different":[174],"effect":[178],"position.":[182],"conclusion,":[184],"method":[186],"value":[191],"EMG":[198],"angle":[202],"has":[208],"good":[209],"provides":[213],"powerful":[215],"tool":[216],"some":[218],"devices":[220],"moment.":[226]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}
