{"id":"https://openalex.org/W2009738053","doi":"https://doi.org/10.1109/ijcnn.2012.6252604","title":"Extracting and selecting discriminative features from high density NIRS-based BCI for numerical cognition","display_name":"Extracting and selecting discriminative features from high density NIRS-based BCI for numerical cognition","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2009738053","doi":"https://doi.org/10.1109/ijcnn.2012.6252604","mag":"2009738053"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2012.6252604","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2012.6252604","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2012 International Joint Conference on Neural Networks (IJCNN)","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/A5100320376","display_name":"Kai Keng Ang","orcid":"https://orcid.org/0000-0002-3053-6311"},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Kai Keng Ang","raw_affiliation_strings":["Agency for Science and Technology And Research, Institute for Infocomm Research, Singapore","Institute for Infocomm Research - Agency for Science and Technology And Research, Singapore"],"affiliations":[{"raw_affiliation_string":"Agency for Science and Technology And Research, Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]},{"raw_affiliation_string":"Institute for Infocomm Research - Agency for Science and Technology And Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112054338","display_name":"Juanhong Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Juanhong Yu","raw_affiliation_strings":["Agency for Science and Technology And Research, Institute for Infocomm Research, Singapore","Institute for Infocomm Research - Agency for Science and Technology And Research, Singapore"],"affiliations":[{"raw_affiliation_string":"Agency for Science and Technology And Research, Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]},{"raw_affiliation_string":"Institute for Infocomm Research - Agency for Science and Technology And Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031778999","display_name":"Cuntai Guan","orcid":"https://orcid.org/0000-0002-0872-3276"},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Cuntai Guan","raw_affiliation_strings":["Agency for Science and Technology And Research, Institute for Infocomm Research, Singapore","Institute for Infocomm Research - Agency for Science and Technology And Research, Singapore"],"affiliations":[{"raw_affiliation_string":"Agency for Science and Technology And Research, Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]},{"raw_affiliation_string":"Institute for Infocomm Research - Agency for Science and Technology And Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100320376"],"corresponding_institution_ids":["https://openalex.org/I3005327000"],"apc_list":null,"apc_paid":null,"fwci":0.9765,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.73032047,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"113","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998999834060669,"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":0.9998999834060669,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9441999793052673,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9380000233650208,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.8422924280166626},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7996795177459717},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7140597701072693},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.635259747505188},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5903977751731873},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5816873908042908},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5707131624221802},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5301260352134705},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5275466442108154},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43956267833709717},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.16788548231124878}],"concepts":[{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.8422924280166626},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7996795177459717},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7140597701072693},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.635259747505188},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5903977751731873},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5816873908042908},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5707131624221802},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5301260352134705},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5275466442108154},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43956267833709717},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.16788548231124878},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/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/ijcnn.2012.6252604","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2012.6252604","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2012 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1521991780","https://openalex.org/W2012003052","https://openalex.org/W2022021629","https://openalex.org/W2049846587","https://openalex.org/W2057311210","https://openalex.org/W2060443602","https://openalex.org/W2063000997","https://openalex.org/W2104946207","https://openalex.org/W2106006415","https://openalex.org/W2115705587","https://openalex.org/W2116604329","https://openalex.org/W2118020555","https://openalex.org/W2122003336","https://openalex.org/W2132549764","https://openalex.org/W2133085637","https://openalex.org/W2133565549","https://openalex.org/W2134478553","https://openalex.org/W2148603752","https://openalex.org/W2149772057","https://openalex.org/W2150469136","https://openalex.org/W2153566817","https://openalex.org/W2154669369","https://openalex.org/W4231299267","https://openalex.org/W4235681452","https://openalex.org/W6677186600","https://openalex.org/W6677564754"],"related_works":["https://openalex.org/W3202969339","https://openalex.org/W4237513258","https://openalex.org/W1994410349","https://openalex.org/W3177028067","https://openalex.org/W2965546495","https://openalex.org/W1913385466","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W2510961579","https://openalex.org/W2106231951"],"abstract_inverted_index":{"Near-Infrared":[0],"Spectroscopy":[1],"(NIRS)-based":[2],"Brain-Computer":[3],"Interface":[4],"(BCI)":[5],"was":[6],"recently":[7],"studied":[8],"for":[9,55,209],"numerical":[10,211],"cognition.":[11,212],"This":[12,77],"study":[13,16,51],"presents":[14,79],"a":[15,80,103,108],"using":[17,92,115,139,148,177,187,196],"high":[18,87,205],"density":[19,57,88,206],"348":[20],"channels":[21,59],"NIRS-based":[22,60,207],"BCI":[23,208],"from":[24,86],"8":[25],"healthy":[26],"subjects":[27],"while":[28],"solving":[29],"mental":[30],"arithmetic":[31],"problems":[32],"with":[33],"two":[34],"difficulty":[35],"levels":[36],"and":[37,45,62,98,102,112,123,163,171,184,201],"the":[38,49,64,67,116,134,143,149,178,193,197],"rest":[39,174],"condition.":[40],"The":[41,131,154,190],"existing":[42,50,188],"feature":[43,199],"extraction":[44,200],"selection":[46,202],"methods":[47],"on":[48,66,142],"were":[52],"presented":[53],"only":[54],"low":[56],"16":[58],"BCI,":[61],"required":[63],"specification":[65],"number":[68],"of":[69,82,105,110,133,161,195],"features":[70,85,114],"to":[71,73,182],"select":[72],"yield":[74],"desirable":[75],"performance.":[76],"paper":[78],"method":[81,104,136,203],"extracting":[83],"discriminative":[84,111],"single-trial":[89,99,144],"NIRS":[90,145],"data":[91,146],"common":[93],"average":[94,159],"reference":[95],"spatial":[96],"filtering":[97],"baseline":[100],"reference,":[101],"automatically":[106],"selecting":[107],"set":[109],"non-redundant":[113],"Mutual":[117],"Information-based":[118],"Rough":[119],"Set":[120],"Reduction":[121],"(MIRSR)":[122],"Supervised":[124],"Pseudo":[125],"Self-":[126],"Evolving":[127],"Cerebellar":[128],"(SPSEC)":[129],"algorithms.":[130],"performance":[132],"proposed":[135,179,198],"is":[137],"evaluated":[138],"5\u00d75-fold":[140],"cross-validations":[141],"collected":[147],"support":[150],"vector":[151],"machine":[152],"classifier.":[153],"results":[155,191],"yielded":[156],"an":[157],"overall":[158],"accuracy":[160],"71.4%":[162],"91.0%":[164],"in":[165,204],"classifying":[166],"hard":[167,172],"versus":[168,173],"easy":[169],"tasks":[170,175],"respectively":[176,186],"method,":[180],"compared":[181],"46.1%":[183],"62.2%":[185],"methods.":[189],"demonstrated":[192],"effectiveness":[194],"assessing":[210]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}