{"id":"https://openalex.org/W2890057045","doi":"https://doi.org/10.1109/access.2018.2869687","title":"Decoding Asynchronous Reaching in Electroencephalography Using Stacked Autoencoders","display_name":"Decoding Asynchronous Reaching in Electroencephalography Using Stacked Autoencoders","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2890057045","doi":"https://doi.org/10.1109/access.2018.2869687","mag":"2890057045"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2869687","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2869687","pdf_url":null,"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":null,"license_id":null,"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://doi.org/10.1109/access.2018.2869687","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005008920","display_name":"Dingyi Pei","orcid":"https://orcid.org/0000-0001-7756-3678"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dingyi Pei","raw_affiliation_strings":["Sensorimotor Control Laboratory, Stevens Institute of Technology, Hoboken, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sensorimotor Control Laboratory, Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079897853","display_name":"Martin Burns","orcid":"https://orcid.org/0000-0003-3068-4442"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Martin Burns","raw_affiliation_strings":["Sensorimotor Control Laboratory, Stevens Institute of Technology, Hoboken, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sensorimotor Control Laboratory, Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079458346","display_name":"R. Chandramouli","orcid":"https://orcid.org/0000-0001-7889-740X"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rajarathnam Chandramouli","raw_affiliation_strings":["Sensorimotor Control Laboratory, Stevens Institute of Technology, Hoboken, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sensorimotor Control Laboratory, Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039030171","display_name":"Ramana Vinjamuri","orcid":"https://orcid.org/0000-0003-1650-5524"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramana Vinjamuri","raw_affiliation_strings":["Sensorimotor Control Laboratory, Stevens Institute of Technology, Hoboken, NJ, USA"],"raw_orcid":"https://orcid.org/0000-0003-1650-5524","affiliations":[{"raw_affiliation_string":"Sensorimotor Control Laboratory, Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I108468826"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.734,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.83830576,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"6","issue":null,"first_page":"52889","last_page":"52898"},"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":0.9983999729156494,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/computer-science","display_name":"Computer science","score":0.7353057861328125},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.7087252736091614},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6996949911117554},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6950284242630005},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6836581230163574},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6739624738693237},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6729064583778381},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6675378680229187},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6665152311325073},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5781514048576355},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5425245761871338},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5344381332397461},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.47124677896499634},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.4705125689506531},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4618609845638275},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3164173364639282},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07780742645263672}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7353057861328125},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.7087252736091614},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6996949911117554},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6950284242630005},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6836581230163574},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6739624738693237},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6729064583778381},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6675378680229187},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6665152311325073},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5781514048576355},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5425245761871338},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5344381332397461},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.47124677896499634},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.4705125689506531},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4618609845638275},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3164173364639282},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07780742645263672},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2869687","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2869687","pdf_url":null,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:81efd2125a25410993cdec2b697e9d5b","is_oa":true,"landing_page_url":"https://doaj.org/article/81efd2125a25410993cdec2b697e9d5b","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 6, Pp 52889-52898 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2869687","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2869687","pdf_url":null,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1498101259","https://openalex.org/W1517327380","https://openalex.org/W1574569851","https://openalex.org/W1604827887","https://openalex.org/W1899504021","https://openalex.org/W1919077608","https://openalex.org/W1971128001","https://openalex.org/W1974451895","https://openalex.org/W1989927577","https://openalex.org/W1991557943","https://openalex.org/W2004894435","https://openalex.org/W2007354835","https://openalex.org/W2008108047","https://openalex.org/W2009558838","https://openalex.org/W2021682909","https://openalex.org/W2023581277","https://openalex.org/W2049404626","https://openalex.org/W2076196856","https://openalex.org/W2080119716","https://openalex.org/W2100495367","https://openalex.org/W2106006415","https://openalex.org/W2110798204","https://openalex.org/W2118872857","https://openalex.org/W2125663054","https://openalex.org/W2138857742","https://openalex.org/W2149378603","https://openalex.org/W2150341604","https://openalex.org/W2151669316","https://openalex.org/W2162959856","https://openalex.org/W2165107043","https://openalex.org/W2165717273","https://openalex.org/W2166706404","https://openalex.org/W2216376285","https://openalex.org/W2611785321","https://openalex.org/W2615531356","https://openalex.org/W2735582123","https://openalex.org/W2952331513","https://openalex.org/W3104195492","https://openalex.org/W4205947740","https://openalex.org/W6631636882","https://openalex.org/W6635927475","https://openalex.org/W6676481782","https://openalex.org/W6678759025","https://openalex.org/W6680300913","https://openalex.org/W6684500011"],"related_works":["https://openalex.org/W3009380723","https://openalex.org/W4387350691","https://openalex.org/W4310873165","https://openalex.org/W2355395139","https://openalex.org/W2794812819","https://openalex.org/W2114217318","https://openalex.org/W2002563186","https://openalex.org/W2587881214","https://openalex.org/W3104072235","https://openalex.org/W2048680804"],"abstract_inverted_index":{"Electroencephalography":[0],"(EEG)-based":[1],"brain-computer":[2],"interfaces":[3],"(BCIs)":[4],"that":[5],"decode":[6],"cortical":[7,73],"activity":[8],"in":[9,31,36,80,138,181],"reaching":[10,34,52],"and":[11,96,108,156,170],"grasping":[12],"movements":[13,35,60],"can":[14,177],"enable":[15],"natural":[16],"upper":[17,39],"limb":[18,40],"motor":[19,47],"control.":[20],"In":[21],"this":[22],"paper,":[23],"we":[24],"studied":[25],"the":[26,37,55,58,71,81],"performance":[27],"of":[28,57,70,83,122,148,174],"stacked":[29,88,142,175],"autoencoders":[30,143,176],"decoding":[32,99],"asynchronous":[33],"dominant":[38],"using":[41,100],"EEG.":[42],"Five":[43],"individuals":[44],"without":[45],"any":[46],"disabilities":[48],"performed":[49],"three":[50],"self-paced":[51],"tasks":[53],"while":[54,144],"endpoints":[56],"arm":[59],"were":[61,75,115,164],"recorded":[62],"with":[63,141,154,162],"a":[64,87],"motion":[65],"tracker.":[66],"Power":[67],"spectral":[68],"densities":[69],"relevant":[72],"signals":[74],"extracted":[76],"among":[77],"eight":[78],"bandwidths":[79],"range":[82],"1-45Hz":[84],"to":[85,126,152,160],"train":[86],"autoencoder.":[89],"For":[90],"comparison,":[91],"convolutional":[92],"neural":[93],"network":[94],"(CNN)":[95],"traditional":[97],"linear":[98,109],"principal":[101],"component":[102],"analysis":[103,111,140],"(PCA)":[104],"for":[105,113],"feature":[106,171],"selection":[107],"discriminant":[110],"(LDA)":[112],"classification":[114,120,146],"also":[116],"used.":[117],"An":[118],"average":[119,145],"accuracy":[121],"79\u00b15.5%":[123],"(best":[124,150,158],"up":[125,151,159],"88\u00b16%)":[127],"was":[128],"achieved":[129],"from":[130],"all":[131],"subjects":[132],"on":[133],"wide":[134],"frequency":[135],"band":[136],"(1-45Hz)":[137],"offline":[139],"accuracies":[147],"68\u00b19.1%":[149],"74\u00b19.1%)":[153],"PCA-LDA":[155],"49\u00b113.8%":[157],"56\u00b17.2%)":[161],"CNN":[163],"achieved.":[165],"The":[166],"simultaneous":[167],"dimensionality":[168],"reduction":[169],"extraction":[172],"capabilities":[173],"have":[178],"significant":[179],"advantages":[180],"BCI":[182],"applications.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}