{"id":"https://openalex.org/W3159473930","doi":"https://doi.org/10.3233/jifs-189851","title":"Comparative classification techniques for identification of brain states using TQWT decomposition","display_name":"Comparative classification techniques for identification of brain states using TQWT decomposition","publication_year":2021,"publication_date":"2021-05-06","ids":{"openalex":"https://openalex.org/W3159473930","doi":"https://doi.org/10.3233/jifs-189851","mag":"3159473930"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-189851","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-189851","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-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/A5039560708","display_name":"Rahul Agrawal","orcid":"https://orcid.org/0000-0002-3129-6698"},"institutions":[{"id":"https://openalex.org/I4210146358","display_name":"Raisoni Group of Institutions","ror":"https://ror.org/03dp11s58","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210146358"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Rahul Agrawal","raw_affiliation_strings":["Department of Electronics Engineering, G H Raisoni College of Engineering, Nagpur"],"affiliations":[{"raw_affiliation_string":"Department of Electronics Engineering, G H Raisoni College of Engineering, Nagpur","institution_ids":["https://openalex.org/I4210146358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015636484","display_name":"Preeti Bajaj","orcid":"https://orcid.org/0000-0002-7759-8026"},"institutions":[{"id":"https://openalex.org/I4210146358","display_name":"Raisoni Group of Institutions","ror":"https://ror.org/03dp11s58","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210146358"]},{"id":"https://openalex.org/I155125381","display_name":"Galgotias University","ror":"https://ror.org/02w8ba206","country_code":"IN","type":"education","lineage":["https://openalex.org/I155125381"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Preeti Bajaj","raw_affiliation_strings":["Department of Electronics Engineering, G H Raisoni College of Engineering, Nagpur","Galgotias University, greater Noida"],"affiliations":[{"raw_affiliation_string":"Department of Electronics Engineering, G H Raisoni College of Engineering, Nagpur","institution_ids":["https://openalex.org/I4210146358"]},{"raw_affiliation_string":"Galgotias University, greater Noida","institution_ids":["https://openalex.org/I155125381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5039560708"],"corresponding_institution_ids":["https://openalex.org/I4210146358"],"apc_list":null,"apc_paid":null,"fwci":2.0976,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.86529049,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"41","issue":"5","first_page":"5287","last_page":"5297"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9952999949455261,"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.7334495782852173},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7231553792953491},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6895537376403809},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6069496870040894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5631358623504639},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49747851490974426},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46415719389915466},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.44708070158958435},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3933943510055542},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32396402955055237}],"concepts":[{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.7334495782852173},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7231553792953491},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6895537376403809},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6069496870040894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5631358623504639},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49747851490974426},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46415719389915466},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.44708070158958435},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3933943510055542},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32396402955055237},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-189851","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-189851","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2001192538","https://openalex.org/W2020149116","https://openalex.org/W2053744708","https://openalex.org/W2064675550","https://openalex.org/W2087555100","https://openalex.org/W2106201488","https://openalex.org/W2112797878","https://openalex.org/W2580194401","https://openalex.org/W2731156650","https://openalex.org/W2892124005","https://openalex.org/W2896248782","https://openalex.org/W2900684886","https://openalex.org/W2901948205","https://openalex.org/W2904357521","https://openalex.org/W2914567046","https://openalex.org/W2916950448","https://openalex.org/W2961638199","https://openalex.org/W2968667829","https://openalex.org/W2979077288","https://openalex.org/W2981077959","https://openalex.org/W2985480298","https://openalex.org/W2987934294","https://openalex.org/W2990352814","https://openalex.org/W3000002325"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W1948992892","https://openalex.org/W2104657898","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W1980100242","https://openalex.org/W2530420969","https://openalex.org/W2051187167","https://openalex.org/W4315815996"],"abstract_inverted_index":{"Brain-Computer":[0],"Interface":[1],"provides":[2],"and":[3,22,95,208],"simplifies":[4],"the":[5,9,34,38,41,80,89,159,170,175,182,219,229],"communication":[6,223],"channel":[7],"for":[8,116,135,144],"physically":[10],"disabled":[11,233],"individuals":[12],"suffering":[13],"from":[14,51],"severe":[15],"brain":[16,20],"injury":[17],"related":[18],"to":[19,25,31],"stroke":[21],"lost":[23],"ability":[24],"speak.":[26],"It":[27,68],"helps":[28],"these":[29],"patients":[30],"connect":[32],"with":[33,140,169,191],"outside":[35],"world.":[36],"In":[37],"proposed":[39],"work,":[40],"electroencephalogram":[42],"signal":[43,76,220],"is":[44,56,69,150],"used":[45],"as":[46,120,122,204],"an":[47,196],"input":[48],"source":[49],"taken":[50],"Bonn":[52],"University":[53],"database":[54],"that":[55,225],"divided":[57],"into":[58,84,221],"three":[59,222],"class":[60],"of":[61,64,91,97,105,109,114,124,128,133,161,198,232],"data":[62,216],"consisting":[63],"247":[65],"samples":[66],"each.":[67],"further":[70],"processed":[71],"by":[72,152,185],"Tunable":[73],"Q-Wavelet":[74],"Transform":[75],"decomposition":[77],"technique":[78,102],"where":[79],"signals":[81],"are":[82,211],"subdivided":[83],"various":[85],"sub-bands":[86,115,134],"depending":[87],"on":[88,181],"value":[90,108,127],"Q-factor,":[92],"redundancy":[93,107,126],"factor,":[94],"number":[96,113,132],"sub-bands.":[98],"A":[99],"novel":[100],"custom":[101],"uses":[103],"Q-factor":[104,123],"3,":[106],"3":[110,129],"&":[111,130],"12":[112],"high":[117],"pass":[118,137],"filtering":[119,138],"well":[121],"1,":[125],"7":[131],"low":[136],"combined":[139],"nine":[141],"statistical":[142],"measures":[143],"feature":[145],"extraction":[146],"purpose.":[147],"The":[148,163,214],"classification":[149],"performed":[151,180],"using":[153,186],"multi-class":[154],"support":[155,192],"vector":[156,193],"machine":[157,194],"giving":[158,195],"accuracy":[160,164,197],"99.59%.":[162],"performs":[165],"best":[166],"when":[167],"compared":[168],"existing":[171],"research":[172],"results":[173],"Furthermore,":[174],"comparative":[176],"study":[177],"has":[178],"been":[179],"same":[183],"dataset":[184],"deep":[187],"neural":[188],"network":[189],"along":[190],"100%.":[199],"Other":[200],"evaluation":[201],"parameters":[202],"such":[203],"precision,":[205],"sensitivity,":[206],"specificity,":[207],"F1":[209],"score":[210],"also":[212],"calculated.":[213],"classified":[215],"help":[217,227],"transform":[218],"messages":[224],"will":[226],"solve":[228],"speech":[230],"impairment":[231],"individuals.":[234]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}