{"id":"https://openalex.org/W3025945094","doi":"https://doi.org/10.1109/tim.2020.2994604","title":"A Feature Extraction Method Using Linear Model Identification of Voltammetric Electronic Tongue","display_name":"A Feature Extraction Method Using Linear Model Identification of Voltammetric Electronic Tongue","publication_year":2020,"publication_date":"2020-05-15","ids":{"openalex":"https://openalex.org/W3025945094","doi":"https://doi.org/10.1109/tim.2020.2994604","mag":"3025945094"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2020.2994604","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.2994604","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Instrumentation and Measurement","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/A5033801004","display_name":"Sanjeev Kumar","orcid":"https://orcid.org/0000-0003-3526-6303"},"institutions":[{"id":"https://openalex.org/I11793825","display_name":"National Institute of Technology Patna","ror":"https://ror.org/056wyhh33","country_code":"IN","type":"education","lineage":["https://openalex.org/I11793825","https://openalex.org/I4210152752"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sanjeev Kumar","raw_affiliation_strings":["Department of Electrical Engineering, National Institute of Technology Patna, Patna, India"],"raw_orcid":"https://orcid.org/0000-0003-3526-6303","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Institute of Technology Patna, Patna, India","institution_ids":["https://openalex.org/I11793825"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086784180","display_name":"Arunangshu Ghosh","orcid":"https://orcid.org/0000-0001-9712-172X"},"institutions":[{"id":"https://openalex.org/I11793825","display_name":"National Institute of Technology Patna","ror":"https://ror.org/056wyhh33","country_code":"IN","type":"education","lineage":["https://openalex.org/I11793825","https://openalex.org/I4210152752"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arunangshu Ghosh","raw_affiliation_strings":["Department of Electrical Engineering, National Institute of Technology Patna, Patna, India"],"raw_orcid":"https://orcid.org/0000-0001-9712-172X","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Institute of Technology Patna, Patna, India","institution_ids":["https://openalex.org/I11793825"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I11793825"],"apc_list":null,"apc_paid":null,"fwci":0.4357,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.5804794,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"69","issue":"11","first_page":"9243","last_page":"9250"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":1.0,"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/T11584","display_name":"Biochemical Analysis and Sensing Techniques","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2916","display_name":"Nutrition and Dietetics"},"field":{"id":"https://openalex.org/fields/29","display_name":"Nursing"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10212","display_name":"Electrochemical sensors and biosensors","score":0.9835000038146973,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/electronic-tongue","display_name":"Electronic tongue","score":0.8397824764251709},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6991806030273438},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6373379230499268},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6216369271278381},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5997257828712463},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.5702922940254211},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5306878089904785},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5006763935089111},{"id":"https://openalex.org/keywords/principal-component-regression","display_name":"Principal component regression","score":0.5004265308380127},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.47958651185035706},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4613855183124542},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4535839855670929},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44278308749198914},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4413035809993744},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4331378638744354},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2573237717151642},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19912055134773254},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1837044358253479}],"concepts":[{"id":"https://openalex.org/C162244969","wikidata":"https://www.wikidata.org/wiki/Q3217351","display_name":"Electronic tongue","level":3,"score":0.8397824764251709},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6991806030273438},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6373379230499268},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6216369271278381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5997257828712463},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.5702922940254211},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5306878089904785},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5006763935089111},{"id":"https://openalex.org/C74887250","wikidata":"https://www.wikidata.org/wiki/Q3455892","display_name":"Principal component regression","level":3,"score":0.5004265308380127},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.47958651185035706},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4613855183124542},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4535839855670929},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44278308749198914},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4413035809993744},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4331378638744354},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2573237717151642},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19912055134773254},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1837044358253479},{"id":"https://openalex.org/C31903555","wikidata":"https://www.wikidata.org/wiki/Q1637030","display_name":"Food science","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C8868529","wikidata":"https://www.wikidata.org/wiki/Q124794","display_name":"Taste","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2020.2994604","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.2994604","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5699999928474426,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G3109895620","display_name":null,"funder_award_id":"ECR/2016/001813","funder_id":"https://openalex.org/F4320334771","funder_display_name":"Science and Engineering Research Board"}],"funders":[{"id":"https://openalex.org/F4320334771","display_name":"Science and Engineering Research Board","ror":"https://ror.org/03ffdsr55"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W652043563","https://openalex.org/W1507780418","https://openalex.org/W1540874374","https://openalex.org/W1569512666","https://openalex.org/W1966406737","https://openalex.org/W1967380646","https://openalex.org/W1968806289","https://openalex.org/W1989157562","https://openalex.org/W1996157147","https://openalex.org/W2001716006","https://openalex.org/W2014567042","https://openalex.org/W2020723966","https://openalex.org/W2025696797","https://openalex.org/W2039469634","https://openalex.org/W2062834966","https://openalex.org/W2064338161","https://openalex.org/W2067096391","https://openalex.org/W2102196224","https://openalex.org/W2111072639","https://openalex.org/W2126012359","https://openalex.org/W2145922707","https://openalex.org/W2147434153","https://openalex.org/W2155100335","https://openalex.org/W2170644082","https://openalex.org/W2171347169","https://openalex.org/W2342432562","https://openalex.org/W2566258672","https://openalex.org/W2736054503","https://openalex.org/W2884210328","https://openalex.org/W2892530094","https://openalex.org/W2915330174","https://openalex.org/W2940201145","https://openalex.org/W4249314718","https://openalex.org/W4389888198"],"related_works":["https://openalex.org/W189486455","https://openalex.org/W2468593193","https://openalex.org/W2981666789","https://openalex.org/W1966115210","https://openalex.org/W2042294628","https://openalex.org/W4396824786","https://openalex.org/W4229916583","https://openalex.org/W2013293448","https://openalex.org/W2770989956","https://openalex.org/W2124794399"],"abstract_inverted_index":{"A":[0,189],"novel":[1],"technique":[2],"of":[3,21,77,82,152,186,195],"feature":[4,139,160,173,205],"extraction":[5,140,161,206],"for":[6,25,43,91,169,179,183],"a":[7,158,172],"voltammetric":[8,57],"electronic":[9,58,187],"tongue":[10],"is":[11,65,85],"presented":[12],"using":[13,49],"system":[14,62],"identification":[15,63],"method":[16,141,162,175],"with":[17,98,150],"the":[18,32,50,56,75,83,95,153,164,180,193],"subsequent":[19],"synthesis":[20],"an":[22],"equivalent":[23,40],"circuit":[24,41,69],"black":[26],"tea":[27,45,78],"and":[28,93,127,163,171],"then":[29,72],"to":[30,100],"predict":[31],"total":[33],"theaflavin":[34],"(TF)":[35],"content":[36,102],"in":[37,103,192,200],"it.":[38],"The":[39,80,137],"parameters":[42,70],"different":[44],"samples":[46],"are":[47,71],"estimated":[48],"current":[51],"response":[52],"data":[53],"obtained":[54,199],"from":[55],"tongue,":[59],"on":[60],"which":[61],"procedure":[64],"applied.":[66],"These":[67],"identified":[68],"treated":[73],"as":[74,109],"features":[76,84,196],"samples.":[79],"efficacy":[81],"corroborated":[86],"by":[87],"developing":[88],"prediction":[89,96,146],"models":[90,107,133],"TF":[92,101],"comparing":[94],"results":[97],"reference":[99],"tea.":[104],"Various":[105],"regression":[106,132],"such":[108],"principal":[110],"component":[111,117],"regression,":[112,115,118,123,126,170],"partial":[113],"least-squares":[114],"independent":[116],"multilayer":[119],"feedforward":[120],"neural":[121],"network":[122],"support":[124],"vector":[125],"extreme":[128],"learning":[129],"machine":[130],"(ELM)-based":[131],"have":[134],"been":[135,198],"evaluated.":[136],"proposed":[138],"performs":[142],"better":[143],"when":[144],"its":[145],"accuracy":[147],"was":[148,176],"compared":[149],"that":[151],"discrete":[154],"wavelet":[155],"transform":[156],"(DWT),":[157],"well-established":[159],"neighborhood":[165],"components":[166],"analysis":[167],"(NCA)":[168],"selection":[174],"introduced":[177],"here":[178],"first":[181],"time":[182],"signal":[184],"processing":[185],"tongue.":[188],"significant":[190],"reduction":[191],"number":[194],"has":[197],"this":[201],"work":[202],"over":[203],"existing":[204],"techniques.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
