{"id":"https://openalex.org/W2059989135","doi":"https://doi.org/10.1109/icpr.2010.915","title":"Decoding Finger Flexion from Electrocorticographic Signals Using a Sparse Gaussian Process","display_name":"Decoding Finger Flexion from Electrocorticographic Signals Using a Sparse Gaussian Process","publication_year":2010,"publication_date":"2010-08-01","ids":{"openalex":"https://openalex.org/W2059989135","doi":"https://doi.org/10.1109/icpr.2010.915","mag":"2059989135"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2010.915","doi":"https://doi.org/10.1109/icpr.2010.915","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2010.915","pdf_url":null,"source":{"id":"https://openalex.org/S4393916651","display_name":"Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition","issn_l":"1041-3278","issn":["1041-3278","1051-4651"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 20th International Conference on Pattern Recognition","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5054141284","display_name":"Zuoguan Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zuoguan Wang","raw_affiliation_strings":["Rensselaer Polytechnic Institute, Troy, NY, USA","Rensselear Polytech. Inst., Troy, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute, Troy, NY, USA","institution_ids":["https://openalex.org/I165799507"]},{"raw_affiliation_string":"Rensselear Polytech. Inst., Troy, NY, USA","institution_ids":["https://openalex.org/I165799507"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076346273","display_name":"Qiang Ji","orcid":"https://orcid.org/0000-0002-4302-2889","observed_orcids":["https://orcid.org/0000-0002-4302-2889"]},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiang Ji","raw_affiliation_strings":["Rensselaer Polytechnic Institute, Troy, NY, USA","Rensselear Polytech. Inst., Troy, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute, Troy, NY, USA","institution_ids":["https://openalex.org/I165799507"]},{"raw_affiliation_string":"Rensselear Polytech. Inst., Troy, NY, USA","institution_ids":["https://openalex.org/I165799507"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060950565","display_name":"Kai Joshua Miller","orcid":"https://orcid.org/0000-0002-6687-6422","observed_orcids":["https://orcid.org/0000-0002-6687-6422"]},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kai J. Miller","raw_affiliation_strings":["Department of Physics, University of Washington, Seattle, WA, USA","Dept. of Phys., Univ. of Washington, Seattle, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Physics, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]},{"raw_affiliation_string":"Dept. of Phys., Univ. of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016183714","display_name":"Gerwin Schalk","orcid":"https://orcid.org/0000-0003-3443-9487","observed_orcids":["https://orcid.org/0000-0003-3443-9487","https://orcid.org/0000-0002-2588-2754"]},"institutions":[{"id":"https://openalex.org/I1339417872","display_name":"Wadsworth Center","ror":"https://ror.org/050kf9c55","country_code":"US","type":"facility","lineage":["https://openalex.org/I1298060332","https://openalex.org/I1339417872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gerwin Schalk","raw_affiliation_strings":["Albany, NY, USA","NYS Dept. of Health, Wadsworth Ctr., Albany, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Albany, NY, USA","institution_ids":[]},{"raw_affiliation_string":"NYS Dept. of Health, Wadsworth Ctr., Albany, NY, USA","institution_ids":["https://openalex.org/I1339417872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.5055,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.92110686,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3756","last_page":"3759"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9945999979972839,"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":0.9945999979972839,"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/T10784","display_name":"Muscle activation and electromyography studies","score":0.0017000000225380063,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.00039999998989515007,"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/brain-computer-interface","display_name":"brain-computer interface","score":0.8759999871253967},{"id":"https://openalex.org/keywords/electrocorticography","display_name":"electrocorticography","score":0.8880000114440918},{"id":"https://openalex.org/keywords/sparse-gaussian-processes","display_name":"sparse Gaussian processes","score":0.8799999952316284},{"id":"https://openalex.org/keywords/nonlinear-decoding","display_name":"nonlinear decoding","score":0.7300000190734863},{"id":"https://openalex.org/keywords/forecast-uncertainty","display_name":"forecast uncertainty","score":0.7099999785423279},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.7710000276565552},{"id":"https://openalex.org/keywords/motor-impairment","display_name":"motor impairment","score":0.5519999861717224},{"id":"https://openalex.org/keywords/high-dimensional-feature-space","display_name":"high-dimensional feature space","score":0.6240000128746033}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.769827663898468},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.76971435546875},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.6815527081489563},{"id":"https://openalex.org/C40743351","wikidata":"https://www.wikidata.org/wiki/Q7002049","display_name":"Neural decoding","level":3,"score":0.5298642516136169},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49339190125465393},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4719772934913635},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.46496087312698364},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41760197281837463},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39343804121017456},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3767397999763489},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3349275588989258},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3033747375011444},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.18580347299575806},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12038153409957886},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2010.915","doi":"https://doi.org/10.1109/icpr.2010.915","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2010.915","pdf_url":null,"source":{"id":"https://openalex.org/S4393916651","display_name":"Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition","issn_l":"1041-3278","issn":["1041-3278","1051-4651"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 20th International Conference on Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1653391263","https://openalex.org/W1746819321","https://openalex.org/W1969957364","https://openalex.org/W1995255811","https://openalex.org/W2023042493","https://openalex.org/W2035552967","https://openalex.org/W2099768828","https://openalex.org/W2106006415","https://openalex.org/W2157424831","https://openalex.org/W4211049957"],"related_works":["https://openalex.org/W2165871462","https://openalex.org/W2034778821","https://openalex.org/W4308245377","https://openalex.org/W2110590434","https://openalex.org/W4391306989","https://openalex.org/W2028037703","https://openalex.org/W2581746893","https://openalex.org/W1995255811","https://openalex.org/W7096901388","https://openalex.org/W2540724345"],"abstract_inverted_index":{"A":[0,27],"brain-computer":[1],"interface":[2],"(BCI)":[3],"creates":[4],"a":[5,31,109,123,158,164,190],"direct":[6],"communication":[7],"pathway":[8],"between":[9],"the":[10,35,101,146,173,182,186],"brain":[11,40],"and":[12,16],"an":[13,46],"external":[14],"device,":[15],"can":[17,113,127,144,178],"thereby":[18],"restore":[19],"function":[20],"in":[21,30,138,172],"people":[22],"with":[23,86,105,130],"severe":[24],"motor":[25],"disabilities.":[26],"core":[28],"component":[29],"BCI":[32],"system":[33],"is":[34,98],"decoding":[36,52,95],"algorithm":[37,96,161],"that":[38,64,97,142,162],"translates":[39],"signals":[41,154],"into":[42],"action":[43],"commands":[44],"of":[45,50,71,80,148,181],"output":[47],"device.":[48],"Most":[49],"current":[51],"algorithms":[53],"are":[54],"based":[55,99],"on":[56,100],"linear":[57,62,120,165],"models":[58,73],"(e.g.,":[59,74],"derived":[60],"using":[61],"regression)":[63],"may":[65],"have":[66],"important":[67,196],"shortcomings.":[68],"The":[69,135],"use":[70],"nonlinear":[72],"neural":[75],"networks)":[76],"could":[77],"overcome":[78],"some":[79],"these":[81],"shortcomings,":[82],"but":[83],"has":[84],"difficulties":[85],"high":[87,131],"dimensional":[88,132],"feature":[89,133],"spaces.":[90],"Here":[91],"we":[92],"propose":[93],"another":[94],"sparse":[102],"gaussian":[103],"process":[104],"pseudo-inputs":[106],"(SPGP).":[107],"As":[108,122],"nonparametric":[110],"method,":[111,125],"it":[112,126],"model":[114],"more":[115,155],"complex":[116],"relationships":[117],"compared":[118],"to":[119],"methods.":[121],"kernel":[124],"readily":[128],"deal":[129],"space.":[134],"evaluations":[136],"shown":[137],"this":[139],"paper":[140],"demonstrate":[141],"SPGP":[143,177,188],"decode":[145],"flexion":[147],"finger":[149],"movements":[150],"from":[151],"electrocorticographic":[152],"(ECoG)":[153],"accurately":[156],"than":[157],"previously":[159],"described":[160],"used":[163],"model.":[166],"In":[167],"addition,":[168],"by":[169],"formulating":[170],"problems":[171],"bayesian":[174],"probabilistic":[175],"framework,":[176],"provide":[179],"estimation":[180],"prediction":[183],"uncertainty.":[184],"Furthermore,":[185],"trained":[187],"offers":[189],"very":[191],"effective":[192],"way":[193],"for":[194],"identifying":[195],"features.":[197]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":3}],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2016-06-24T00:00:00"}