{"id":"https://openalex.org/W3031300190","doi":"https://doi.org/10.1109/smc42975.2020.9283028","title":"EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain\u2013Machine Interfaces","display_name":"EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain\u2013Machine Interfaces","publication_year":2020,"publication_date":"2020-10-11","ids":{"openalex":"https://openalex.org/W3031300190","doi":"https://doi.org/10.1109/smc42975.2020.9283028","mag":"3031300190"},"language":"en","primary_location":{"id":"doi:10.1109/smc42975.2020.9283028","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc42975.2020.9283028","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/20.500.11850/506146","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035288047","display_name":"Thorir Mar Ingolfsson","orcid":"https://orcid.org/0000-0002-5282-324X"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Thorir Mar Ingolfsson","raw_affiliation_strings":["ETH Zurich, Switzerland","ETH Z\u00fcrich,Dept. EE & IT,Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"ETH Z\u00fcrich,Dept. EE & IT,Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068274229","display_name":"Michael Hersche","orcid":"https://orcid.org/0000-0003-3065-7639"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Michael Hersche","raw_affiliation_strings":["ETH Zurich, Switzerland","ETH Z\u00fcrich,Dept. EE & IT,Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"ETH Z\u00fcrich,Dept. EE & IT,Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058682991","display_name":"Xiaying Wang","orcid":"https://orcid.org/0000-0003-3467-5033"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Xiaying Wang","raw_affiliation_strings":["ETH Zurich, Switzerland","ETH Z\u00fcrich,Dept. EE & IT,Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"ETH Z\u00fcrich,Dept. EE & IT,Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017323255","display_name":"Nobuaki Kobayashi","orcid":"https://orcid.org/0000-0002-7064-320X"},"institutions":[{"id":"https://openalex.org/I104946051","display_name":"Nihon University","ror":"https://ror.org/05jk51a88","country_code":"JP","type":"education","lineage":["https://openalex.org/I104946051"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nobuaki Kobayashi","raw_affiliation_strings":["College of Science and Technology, Nihon University, Japan","Nihon University,College of Science and Technology,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Science and Technology, Nihon University, Japan","institution_ids":["https://openalex.org/I104946051"]},{"raw_affiliation_string":"Nihon University,College of Science and Technology,Japan","institution_ids":["https://openalex.org/I104946051"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025399641","display_name":"Lukas Cavigelli","orcid":"https://orcid.org/0000-0003-1767-7715"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Lukas Cavigelli","raw_affiliation_strings":["ETH Zurich, Switzerland","Huawei Technologies, Zurich Research Center, Switzerland","ETH Z\u00fcrich,Dept. EE & IT,Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"Huawei Technologies, Zurich Research Center, Switzerland","institution_ids":[]},{"raw_affiliation_string":"ETH Z\u00fcrich,Dept. EE & IT,Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043408422","display_name":"Luca Benini","orcid":"https://orcid.org/0000-0001-8068-3806"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Luca Benini","raw_affiliation_strings":["ETH Zurich, Switzerland","ETH Z\u00fcrich,Dept. EE & IT,Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"ETH Z\u00fcrich,Dept. EE & IT,Switzerland","institution_ids":["https://openalex.org/I35440088"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3707,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.79855483,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2958","last_page":"2965"},"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8266067504882812},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.7825754880905151},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.6371930837631226},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6110900640487671},{"id":"https://openalex.org/keywords/memory-footprint","display_name":"Memory footprint","score":0.5341412425041199},{"id":"https://openalex.org/keywords/motor-imagery","display_name":"Motor imagery","score":0.5227646827697754},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5147154927253723},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5110939145088196},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4945232570171356},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.49063006043434143},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42410987615585327},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38471370935440063}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8266067504882812},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.7825754880905151},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.6371930837631226},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6110900640487671},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.5341412425041199},{"id":"https://openalex.org/C54808283","wikidata":"https://www.wikidata.org/wiki/Q6918191","display_name":"Motor imagery","level":4,"score":0.5227646827697754},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5147154927253723},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5110939145088196},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4945232570171356},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.49063006043434143},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42410987615585327},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38471370935440063},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":8,"locations":[{"id":"doi:10.1109/smc42975.2020.9283028","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc42975.2020.9283028","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},{"id":"pmh:oai:www.research-collection.ethz.ch:20.500.11850/506146","is_oa":true,"landing_page_url":"http://hdl.handle.net/20.500.11850/506146","pdf_url":null,"source":{"id":"https://openalex.org/S4306402302","display_name":"Repository for Publications and Research Data (ETH Zurich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I35440088","host_organization_name":"ETH Zurich","host_organization_lineage":["https://openalex.org/I35440088"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"info:eu-repo/semantics/acceptedVersion"},{"id":"pmh:oai:arXiv.org:2006.00622","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2006.00622","pdf_url":"https://arxiv.org/pdf/2006.00622","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3031300190","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2006.00622.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:www.research-collection.ethz.ch:20.500.11850/457103","is_oa":true,"landing_page_url":"http://hdl.handle.net/20.500.11850/457103","pdf_url":null,"source":{"id":"https://openalex.org/S4306402302","display_name":"Repository for Publications and Research Data (ETH Zurich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I35440088","host_organization_name":"ETH Zurich","host_organization_lineage":["https://openalex.org/I35440088"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"doi:10.48550/arxiv.2006.00622","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2006.00622","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"doi:10.17023/vmhm-3r31","is_oa":true,"landing_page_url":"https://doi.org/10.17023/vmhm-3r31","pdf_url":null,"source":{"id":"https://openalex.org/S7407051697","display_name":"IEEE RESOURCE CENTERS","issn_l":null,"issn":[],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"doi:10.3929/ethz-b-000457103","is_oa":true,"landing_page_url":"https://doi.org/10.3929/ethz-b-000457103","pdf_url":null,"source":{"id":"https://openalex.org/S7407051236","display_name":"ETH Z\u00fcrich Research Collection","issn_l":null,"issn":[],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:www.research-collection.ethz.ch:20.500.11850/506146","is_oa":true,"landing_page_url":"http://hdl.handle.net/20.500.11850/506146","pdf_url":null,"source":{"id":"https://openalex.org/S4306402302","display_name":"Repository for Publications and Research Data (ETH Zurich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I35440088","host_organization_name":"ETH Zurich","host_organization_lineage":["https://openalex.org/I35440088"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"info:eu-repo/semantics/acceptedVersion"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W2119163516","https://openalex.org/W2194775991","https://openalex.org/W2511730936","https://openalex.org/W2559463885","https://openalex.org/W2585506822","https://openalex.org/W2741907166","https://openalex.org/W2757196798","https://openalex.org/W2784160801","https://openalex.org/W2792764867","https://openalex.org/W2794345050","https://openalex.org/W2804957865","https://openalex.org/W2908939695","https://openalex.org/W2909259964","https://openalex.org/W2949382160","https://openalex.org/W2951648764","https://openalex.org/W2954607156","https://openalex.org/W2962840532","https://openalex.org/W2963258090","https://openalex.org/W2974596145","https://openalex.org/W2989802020","https://openalex.org/W2990721662","https://openalex.org/W2998481005","https://openalex.org/W3007729836","https://openalex.org/W3014233359","https://openalex.org/W3016214704","https://openalex.org/W3017932985","https://openalex.org/W3020547132","https://openalex.org/W3041051645","https://openalex.org/W3096176982","https://openalex.org/W3102455230","https://openalex.org/W3104324110","https://openalex.org/W6679555981","https://openalex.org/W6725739302","https://openalex.org/W6744331365","https://openalex.org/W6749825310","https://openalex.org/W6765264953","https://openalex.org/W6963588625"],"related_works":["https://openalex.org/W3112695512","https://openalex.org/W3102455230","https://openalex.org/W2990721662","https://openalex.org/W2951695220","https://openalex.org/W2964252002","https://openalex.org/W3206997847","https://openalex.org/W2897035501","https://openalex.org/W3125533742","https://openalex.org/W3129964406","https://openalex.org/W2990809856","https://openalex.org/W2897351303","https://openalex.org/W2557301950","https://openalex.org/W3184616926","https://openalex.org/W2945763771","https://openalex.org/W2906965193","https://openalex.org/W2982852215","https://openalex.org/W3136247184","https://openalex.org/W2895717704","https://openalex.org/W3139277833","https://openalex.org/W2583984586"],"abstract_inverted_index":{"In":[0,67],"recent":[1],"years,":[2],"deep":[3],"learning":[4],"(DL)":[5],"has":[6],"contributed":[7],"significantly":[8],"to":[9,47,141],"the":[10,64,108,113,130,139,146,151,183],"improvement":[11],"of":[12,37,148,153,192],"motor-imagery":[13],"brain-machine":[14],"interfaces":[15],"(MI-BMIs)":[16],"based":[17],"on":[18,104,112,150,187],"electroencephalography":[19],"(EEG).":[20],"While":[21],"achieving":[22],"high":[23],"classification":[24,103,123],"accuracy,":[25],"DL":[26],"models":[27],"have":[28],"also":[29],"grown":[30],"in":[31,125],"size,":[32],"requiring":[33,84],"a":[34,44,73,158,190],"vast":[35],"amount":[36],"memory":[38,90],"and":[39,58,92],"computational":[40,94],"resources.":[41],"This":[42],"poses":[43],"major":[45],"challenge":[46],"an":[48],"embedded":[49,102],"BMI":[50],"solution":[51],"that":[52,79,119,174],"guarantees":[53],"user":[54],"privacy,":[55],"reduced":[56],"latency,":[57],"low":[59,89,93],"power":[60],"consumption":[61],"by":[62,189],"processing":[63],"data":[65],"locally.":[66],"this":[68],"paper,":[69],"we":[70,136,144],"propose":[71],"EEG-TCNet,":[72],"novel":[74],"temporal":[75],"convolutional":[76],"network":[77,132],"(TCN)":[78],"achieves":[80,121],"outstanding":[81],"accuracy":[82,124,140],"while":[83],"few":[85],"trainable":[86],"parameters.":[87],"Its":[88],"footprint":[91],"complexity":[95],"for":[96,101],"inference":[97],"make":[98],"it":[99],"suitable":[100],"resource-limited":[105],"devices":[106],"at":[107],"edge.":[109],"Experimental":[110],"results":[111,172],"BCI":[114,155],"Competition":[115],"IV-2a":[116],"dataset":[117],"show":[118],"EEG-TCNet":[120,149,175],"77.35%":[122],"4-class":[126],"MI.":[127],"By":[128],"finding":[129],"optimal":[131],"hyperparameters":[133],"per":[134],"subject,":[135],"further":[137],"improve":[138],"83.84%.":[142],"Finally,":[143],"demonstrate":[145],"versatility":[147],"Mother":[152],"All":[154],"Benchmarks":[156],"(MOABB),":[157],"large":[159],"scale":[160],"test":[161],"benchmark":[162],"containing":[163],"12":[164],"different":[165],"EEG":[166],"datasets":[167],"with":[168],"MI":[169],"experiments.":[170],"The":[171],"indicate":[173],"successfully":[176],"generalizes":[177],"beyond":[178],"one":[179],"single":[180],"dataset,":[181],"outperforming":[182],"current":[184],"state-of-the-art":[185],"(SoA)":[186],"MOABB":[188],"meta-effect":[191],"0.25.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
