{"id":"https://openalex.org/W2918941196","doi":"https://doi.org/10.1109/tencon.2018.8650433","title":"Decoding ECoG Signal with Deep Learning Model Based on LSTM","display_name":"Decoding ECoG Signal with Deep Learning Model Based on LSTM","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2918941196","doi":"https://doi.org/10.1109/tencon.2018.8650433","mag":"2918941196"},"language":"en","primary_location":{"id":"doi:10.1109/tencon.2018.8650433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2018.8650433","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2018 - 2018 IEEE Region 10 Conference","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/A5005169670","display_name":"Anming Du","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Anming Du","raw_affiliation_strings":["Dept. of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102937558","display_name":"Shuqin Yang","orcid":"https://orcid.org/0000-0002-6809-2963"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuqin Yang","raw_affiliation_strings":["Dept. of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Dept. of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100747519","display_name":"Weijia Liu","orcid":"https://orcid.org/0000-0002-7684-5777"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weijia Liu","raw_affiliation_strings":["Schol. of Bell Honors, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Schol. of Bell Honors, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088237102","display_name":"Haiping Huang","orcid":"https://orcid.org/0000-0002-4392-3599"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiping Huang","raw_affiliation_strings":["Dept. of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5005169670"],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":null,"apc_paid":null,"fwci":0.4938,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.64139188,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"0430","last_page":"0435"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"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/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular 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/T10784","display_name":"Muscle activation and electromyography studies","score":0.9865000247955322,"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":0.834705114364624},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6547192335128784},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6134491562843323},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.5852321982383728},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.5793064832687378},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5770301222801208},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5304343700408936},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.496643602848053},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4913841784000397},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.48026537895202637},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43337318301200867},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3869503140449524},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.33821606636047363},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.13326576352119446}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.834705114364624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6547192335128784},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6134491562843323},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.5852321982383728},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.5793064832687378},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5770301222801208},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5304343700408936},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.496643602848053},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4913841784000397},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.48026537895202637},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43337318301200867},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3869503140449524},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33821606636047363},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.13326576352119446},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C129307140","wikidata":"https://www.wikidata.org/wiki/Q6795880","display_name":"Maximum bubble pressure method","level":3,"score":0.0},{"id":"https://openalex.org/C157915830","wikidata":"https://www.wikidata.org/wiki/Q2928001","display_name":"Bubble","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon.2018.8650433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2018.8650433","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2018 - 2018 IEEE Region 10 Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8100000023841858,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W202232339","https://openalex.org/W1982312747","https://openalex.org/W2034778821","https://openalex.org/W2119163516","https://openalex.org/W2293634267","https://openalex.org/W2581746893","https://openalex.org/W2591008872","https://openalex.org/W2754265241","https://openalex.org/W2919115771"],"related_works":["https://openalex.org/W3202969339","https://openalex.org/W4237513258","https://openalex.org/W2044053727","https://openalex.org/W1994410349","https://openalex.org/W3177028067","https://openalex.org/W1913385466","https://openalex.org/W2914170859","https://openalex.org/W2889342546","https://openalex.org/W2015048155","https://openalex.org/W2106231951"],"abstract_inverted_index":{"Currently,":[0],"brain-computer":[1],"interface":[2],"technology":[3],"(BCI)":[4],"has":[5],"been":[6],"widely":[7],"used":[8],"in":[9],"brain":[10],"disease":[11],"diagnosis":[12],"and":[13,38,47,93,113],"motor":[14],"disabilities":[15],"recovery.":[16],"In":[17],"this":[18,123],"paper,":[19],"it":[20,43,65,125],"proposes":[21],"a":[22,67],"novel":[23],"scheme":[24],"that":[25],"using":[26],"deep":[27,69],"learning":[28,70,116],"model":[29,71],"based":[30],"on":[31],"Long":[32],"Short-Term":[33],"Memory":[34],"(LSTM)":[35],"to":[36,58,72,88,128],"extract":[37],"classify":[39,73],"ECoG":[40,46,74,91,102],"signals.":[41],"First,":[42],"preprocesses":[44],"the":[45,51,59,63,79,120,132],"voltage":[48],"signal":[49],"when":[50],"subject's":[52],"finger":[53],"is":[54,86,106,126],"bent.":[55],"Second,":[56],"according":[57],"time":[60],"characteristics":[61],"of":[62,81,122,131],"ECoG,":[64],"designs":[66],"6-layer":[68],"signals":[75],"directly,":[76],"while":[77],"avoiding":[78],"time-consuming":[80],"feature":[82],"extraction.":[83],"This":[84],"method":[85],"applied":[87,127],"an":[89],"open":[90],"dataset":[92],"experimental":[94],"results":[95],"achieve":[96],"83.3%":[97],"accuracy":[98,105],"over":[99],"5":[100],"categorical":[101],"data.":[103],"The":[104],"significantly":[107],"higher":[108],"than":[109],"traditional":[110],"linear":[111],"analysis":[112],"ordinary":[114],"machine":[115],"methods.":[117],"To":[118],"demonstrated":[119],"feasibility":[121],"proposal,":[124],"real-time":[129],"control":[130],"mechanical":[133],"arm.":[134]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-25T21:42:39.735039","created_date":"2025-10-10T00:00:00"}