{"id":"https://openalex.org/W3045009797","doi":"https://doi.org/10.1109/access.2020.3011185","title":"Encoding Rich Frequencies for Classification of Stroke Patients EEG Signals","display_name":"Encoding Rich Frequencies for Classification of Stroke Patients EEG Signals","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3045009797","doi":"https://doi.org/10.1109/access.2020.3011185","mag":"3045009797"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3011185","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3011185","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09145945.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09145945.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022920652","display_name":"Fawaz Sammani","orcid":"https://orcid.org/0000-0002-7659-4410"},"institutions":[{"id":"https://openalex.org/I173029219","display_name":"Multimedia University","ror":"https://ror.org/04zrbnc33","country_code":"MY","type":"education","lineage":["https://openalex.org/I173029219"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Sammani Fawaz","raw_affiliation_strings":["Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia","institution_ids":["https://openalex.org/I173029219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010387108","display_name":"Kok Swee Sim","orcid":"https://orcid.org/0000-0003-2976-8825"},"institutions":[{"id":"https://openalex.org/I173029219","display_name":"Multimedia University","ror":"https://ror.org/04zrbnc33","country_code":"MY","type":"education","lineage":["https://openalex.org/I173029219"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Kok Swee Sim","raw_affiliation_strings":["Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia"],"raw_orcid":"https://orcid.org/0000-0003-2976-8825","affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia","institution_ids":["https://openalex.org/I173029219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053906728","display_name":"Shing Chiang Tan","orcid":"https://orcid.org/0000-0002-1267-1894"},"institutions":[{"id":"https://openalex.org/I173029219","display_name":"Multimedia University","ror":"https://ror.org/04zrbnc33","country_code":"MY","type":"education","lineage":["https://openalex.org/I173029219"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Shing Chiang Tan","raw_affiliation_strings":["Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia"],"raw_orcid":"https://orcid.org/0000-0002-1267-1894","affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia","institution_ids":["https://openalex.org/I173029219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I173029219"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.5414,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.82128938,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"8","issue":null,"first_page":"135811","last_page":"135820"},"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":0.9968000054359436,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"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/computer-science","display_name":"Computer science","score":0.7213441133499146},{"id":"https://openalex.org/keywords/fast-fourier-transform","display_name":"Fast Fourier transform","score":0.6866852641105652},{"id":"https://openalex.org/keywords/stroke","display_name":"Stroke (engine)","score":0.6424992680549622},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5414855480194092},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5360916256904602},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.5196551084518433},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5155129432678223},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.48251792788505554},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4477861821651459},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.42356395721435547},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.414266973733902},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3736553192138672},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3311503827571869},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32821333408355713},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2498568892478943},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.206800639629364},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.16312426328659058},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.14908850193023682}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7213441133499146},{"id":"https://openalex.org/C75172450","wikidata":"https://www.wikidata.org/wiki/Q623950","display_name":"Fast Fourier transform","level":2,"score":0.6866852641105652},{"id":"https://openalex.org/C2780645631","wikidata":"https://www.wikidata.org/wiki/Q671554","display_name":"Stroke (engine)","level":2,"score":0.6424992680549622},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5414855480194092},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5360916256904602},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.5196551084518433},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5155129432678223},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.48251792788505554},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4477861821651459},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.42356395721435547},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.414266973733902},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3736553192138672},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3311503827571869},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32821333408355713},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2498568892478943},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.206800639629364},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16312426328659058},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.14908850193023682},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","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},{"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/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2020.3011185","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3011185","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09145945.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:shdl.mmu.edu.my:7905","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196753","display_name":"Siti Hasmah Digital Library-MMU Institutiona Repository (Multimedia University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I173029219","host_organization_name":"Multimedia University","host_organization_lineage":["https://openalex.org/I173029219"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"pmh:oai:doaj.org/article:33e70fac7b524a3ab735028864a4c602","is_oa":true,"landing_page_url":"https://doaj.org/article/33e70fac7b524a3ab735028864a4c602","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 135811-135820 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3011185","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3011185","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09145945.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3045009797.pdf","grobid_xml":"https://content.openalex.org/works/W3045009797.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1959608418","https://openalex.org/W1980615352","https://openalex.org/W2016555609","https://openalex.org/W2064675550","https://openalex.org/W2112796928","https://openalex.org/W2125389028","https://openalex.org/W2131774270","https://openalex.org/W2164082066","https://openalex.org/W2194775991","https://openalex.org/W2244991220","https://openalex.org/W2290410864","https://openalex.org/W2345029937","https://openalex.org/W2390253628","https://openalex.org/W2414309931","https://openalex.org/W2472261436","https://openalex.org/W2513213398","https://openalex.org/W2559463885","https://openalex.org/W2561324334","https://openalex.org/W2599251041","https://openalex.org/W2614288205","https://openalex.org/W2734667672","https://openalex.org/W2769045025","https://openalex.org/W2770384163","https://openalex.org/W2776446922","https://openalex.org/W2797669432","https://openalex.org/W2801798116","https://openalex.org/W2806591294","https://openalex.org/W2920295506","https://openalex.org/W2962760235","https://openalex.org/W2963355311","https://openalex.org/W2963470893","https://openalex.org/W3091905774","https://openalex.org/W3102455230","https://openalex.org/W3105605673","https://openalex.org/W4294643831","https://openalex.org/W4297726864","https://openalex.org/W4320013936","https://openalex.org/W6640963894","https://openalex.org/W6678815747","https://openalex.org/W6745560452","https://openalex.org/W6760244434","https://openalex.org/W6783596713","https://openalex.org/W7046306310"],"related_works":["https://openalex.org/W4327521644","https://openalex.org/W2922348724","https://openalex.org/W2978884468","https://openalex.org/W200322357","https://openalex.org/W3132558499","https://openalex.org/W2130428257","https://openalex.org/W2005846134","https://openalex.org/W4308951944","https://openalex.org/W2168413811","https://openalex.org/W2369237035"],"abstract_inverted_index":{"The":[0,152],"stroke,":[1],"which":[2,89],"is":[3],"a":[4,16,38,69,75,158],"sudden":[5],"cut":[6],"in":[7,11,106,128,161],"the":[8,12,34,43,52,100,107,111,180],"blood":[9],"supply":[10],"brain,":[13],"has":[14,20],"become":[15],"severe":[17],"phenomenon.":[18],"It":[19,170],"affected":[21],"around":[22],"15":[23],"million":[24],"people":[25],"annually":[26],"worldwide.":[27],"Methods":[28],"of":[29,45,51,86,182],"stroke":[30,64,163,183],"discovery":[31],"and":[32,73,91,110,119,126],"monitoring":[33],"patient's":[35],"recovery":[36],"are":[37,123],"long":[39],"process,":[40],"ranging":[41],"from":[42],"analysis":[44],"medical":[46,159],"images":[47,165],"to":[48,62,117,178],"frequent":[49],"reporting":[50],"patients":[53],"for":[54,175],"progress":[55,181],"assessment.":[56],"In":[57,81],"this":[58],"paper,":[59],"we":[60],"aim":[61],"process":[63],"patient":[65],"EEG":[66,77],"signals":[67],"by":[68,132,143],"deep":[70],"learning":[71,144],"approach,":[72],"classify":[74],"given":[76],"signal":[78,95],"into":[79],"stroke/non-stroke.":[80],"particular,":[82],"our":[83,138,149],"model":[84,139,154],"consists":[85],"several":[87,141],"sub-modules":[88],"convert":[90],"re-model":[92],"widely":[93],"used":[94],"processing":[96],"techniques":[97],"such":[98],"as":[99],"Fast":[101,113],"Fourier":[102,114],"Transform":[103,115],"(FFT),":[104],"Convolution":[105],"Frequency":[108],"Domain":[109],"Inverse":[112],"(IFFT)":[116],"learnable":[118],"differentiable":[120],"functions":[121],"that":[122,137],"completely":[124],"learned":[125],"optimized":[127],"an":[129],"end-to-end":[130],"manner":[131],"neural":[133],"networks.":[134],"We":[135],"demonstrate":[136],"outperforms":[140],"baselines":[142],"rich":[145],"frequency":[146],"features":[147],"through":[148],"proposed":[150,153],"model.":[151],"could":[155],"potentially":[156],"assist":[157],"doctor":[160],"analyzing":[162],"brain":[164],"with":[166],"high":[167],"accuracy":[168],"rates.":[169],"can":[171],"also":[172],"be":[173],"useful":[174],"rehabilitation":[176],"centers":[177],"monitor":[179],"patients.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}