{"id":"https://openalex.org/W3216780906","doi":"https://doi.org/10.1109/rfid-ta53372.2021.9617423","title":"An RFID-Based BCI System for Emotion Detection Using EEG patterns","display_name":"An RFID-Based BCI System for Emotion Detection Using EEG patterns","publication_year":2021,"publication_date":"2021-10-06","ids":{"openalex":"https://openalex.org/W3216780906","doi":"https://doi.org/10.1109/rfid-ta53372.2021.9617423","mag":"3216780906"},"language":"en","primary_location":{"id":"doi:10.1109/rfid-ta53372.2021.9617423","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rfid-ta53372.2021.9617423","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on RFID Technology and Applications (RFID-TA)","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/A5079970078","display_name":"Anju Mishra","orcid":"https://orcid.org/0000-0003-4485-1520"},"institutions":[{"id":"https://openalex.org/I191972202","display_name":"Amity University","ror":"https://ror.org/02n9z0v62","country_code":"IN","type":"education","lineage":["https://openalex.org/I191972202"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Anju Mishra","raw_affiliation_strings":["Amity School of Engineering & Technology, Amity University Uttar Pradesh, Noida, India"],"affiliations":[{"raw_affiliation_string":"Amity School of Engineering & Technology, Amity University Uttar Pradesh, Noida, India","institution_ids":["https://openalex.org/I191972202"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053510344","display_name":"Archana Singh","orcid":"https://orcid.org/0000-0001-5365-6351"},"institutions":[{"id":"https://openalex.org/I191972202","display_name":"Amity University","ror":"https://ror.org/02n9z0v62","country_code":"IN","type":"education","lineage":["https://openalex.org/I191972202"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Archana Singh","raw_affiliation_strings":["Amity School of Engineering & Technology, Amity University Uttar Pradesh, Noida, India"],"affiliations":[{"raw_affiliation_string":"Amity School of Engineering & Technology, Amity University Uttar Pradesh, Noida, India","institution_ids":["https://openalex.org/I191972202"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052929609","display_name":"Amit Ujlayan","orcid":"https://orcid.org/0000-0002-6045-8385"},"institutions":[{"id":"https://openalex.org/I72769676","display_name":"Gautam Buddha University","ror":"https://ror.org/026cfwd52","country_code":"IN","type":"education","lineage":["https://openalex.org/I72769676"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Amit Ujlayan","raw_affiliation_strings":["School of Vocational Studies and Applied Sciences, Gautam Buddha University, Greater Noida, India"],"affiliations":[{"raw_affiliation_string":"School of Vocational Studies and Applied Sciences, Gautam Buddha University, Greater Noida, India","institution_ids":["https://openalex.org/I72769676"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5079970078"],"corresponding_institution_ids":["https://openalex.org/I191972202"],"apc_list":null,"apc_paid":null,"fwci":0.1165,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.43465728,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"5","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9997000098228455,"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":0.9997000098228455,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/electroencephalography","display_name":"Electroencephalography","score":0.7838574647903442},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7337621450424194},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.7308483123779297},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5701541900634766},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5621647834777832},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5027725696563721},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.46230757236480713},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.42508190870285034},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4033304452896118},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.12348932027816772}],"concepts":[{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.7838574647903442},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7337621450424194},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.7308483123779297},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5701541900634766},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5621647834777832},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5027725696563721},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.46230757236480713},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.42508190870285034},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4033304452896118},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.12348932027816772},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C157915830","wikidata":"https://www.wikidata.org/wiki/Q2928001","display_name":"Bubble","level":2,"score":0.0},{"id":"https://openalex.org/C129307140","wikidata":"https://www.wikidata.org/wiki/Q6795880","display_name":"Maximum bubble pressure method","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/rfid-ta53372.2021.9617423","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rfid-ta53372.2021.9617423","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on RFID Technology and Applications (RFID-TA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1987809737","https://openalex.org/W2002055708","https://openalex.org/W2041280856","https://openalex.org/W2063767522","https://openalex.org/W2064770205","https://openalex.org/W2081724542","https://openalex.org/W2096317114","https://openalex.org/W2149628368","https://openalex.org/W2298261874","https://openalex.org/W2625929003","https://openalex.org/W2626639109","https://openalex.org/W2786768213","https://openalex.org/W2790404832","https://openalex.org/W2790543161","https://openalex.org/W2792523725","https://openalex.org/W2924944963","https://openalex.org/W2954060546","https://openalex.org/W3009689205","https://openalex.org/W3030703790","https://openalex.org/W3083985131","https://openalex.org/W3089423349","https://openalex.org/W3112227555","https://openalex.org/W3114802091","https://openalex.org/W6750052068","https://openalex.org/W6782932696"],"related_works":["https://openalex.org/W3202969339","https://openalex.org/W4237513258","https://openalex.org/W1994410349","https://openalex.org/W3177028067","https://openalex.org/W1913385466","https://openalex.org/W2106231951","https://openalex.org/W2032664813","https://openalex.org/W2095030957","https://openalex.org/W2066827917","https://openalex.org/W2884201223"],"abstract_inverted_index":{"Emotion":[0,84],"categorization":[1],"using":[2,127,140],"electroencephalogram":[3],"(EEG)":[4],"signals":[5],"can":[6,28,198],"be":[7,29,200],"a":[8,22,26,58,93,156,184,189],"difficult":[9],"task":[10],"and":[11,41,54,102,121,163,197],"requires":[12],"cognitive":[13],"analysis":[14],"of":[15,36,50,113,172,209],"EEG":[16,87,119,132,168],"patterns":[17,120,133],"for":[18,83,154,166],"mapping":[19],"them":[20,56,123],"to":[21,46,105,160,176,192],"specific":[23],"emotion.":[24,109,186],"Such":[25],"system":[27,82,91,96,115,187],"utilized":[30],"in":[31,43,202],"many":[32,67],"ways.":[33],"The":[34,89,110,170],"concept":[35],"emotions":[37],"is":[38,61,64,152,174,206],"itself":[39],"complex":[40],"fuzzy":[42,94],"nature.":[44],"Therefore,":[45],"handle":[47],"the":[48,100,107,114,177,181,193,207,210],"fuzziness":[49],"individual\u2019s":[51,108,125],"emotional":[52],"experiences":[53],"presenting":[55],"as":[57,183],"discrete":[59,185],"emotion":[60],"all":[62],"that":[63,98],"required":[65],"by":[66,144],"EEG-based":[68],"brain":[69],"computer":[70],"interface":[71],"(BCI)":[72],"systems.":[73],"In":[74],"this":[75],"work,":[76],"we":[77],"present":[78],"an":[79],"RFID-based":[80],"BCI":[81],"classification":[85],"from":[86],"patterns.":[88,169],"presented":[90],"uses":[92],"inference":[95],"(FIS)":[97],"utilizes":[99],"valence":[101,162],"arousal":[103,164],"modalities":[104],"model":[106,159],"major":[111],"steps":[112],"are:":[116],"preprocessing":[117],"recorded":[118],"saving":[122],"with":[124],"identification":[126],"RFID":[128],"tags,":[129],"then":[130],"preprocessed":[131],"are":[134],"decomposed":[135],"into":[136],"different":[137],"frequency":[138],"bands":[139],"wavelet":[141],"decomposition,":[142],"followed":[143],"feature":[145,148],"extraction":[146],"step,":[147],"matrix":[149],"so":[150],"obtained":[151],"used":[153,201],"training":[155],"k-nearest":[157],"neighbor":[158],"generate":[161],"values":[165],"given":[167],"output":[171],"KNN":[173],"fed":[175],"FIS":[178],"which":[179,205],"models":[180],"pattern":[182],"gives":[188],"new":[190],"dimension":[191],"BCI-based":[194],"content":[195],"servers":[196],"also":[199],"healthcare":[203],"services":[204],"need":[208],"hour.":[211]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}