{"id":"https://openalex.org/W2782654763","doi":"https://doi.org/10.1109/icsai.2017.8248445","title":"Epileptic seizure auto-detection using deep learning method","display_name":"Epileptic seizure auto-detection using deep learning method","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2782654763","doi":"https://doi.org/10.1109/icsai.2017.8248445","mag":"2782654763"},"language":"en","primary_location":{"id":"doi:10.1109/icsai.2017.8248445","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsai.2017.8248445","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 4th International Conference on Systems and Informatics (ICSAI)","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/A5103257788","display_name":"Yuzhen Cao","orcid":"https://orcid.org/0000-0002-3512-4447"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuzhen Cao","raw_affiliation_strings":["School of Precision Instrument and Opto-electronics Engineering, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Precision Instrument and Opto-electronics Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004910474","display_name":"Yixiang Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixiang Guo","raw_affiliation_strings":["School of Precision Instrument and Opto-electronics Engineering, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Precision Instrument and Opto-electronics Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029714740","display_name":"Hui Yu","orcid":"https://orcid.org/0000-0002-8511-7296"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Yu","raw_affiliation_strings":["School of Precision Instrument and Opto-electronics Engineering, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Precision Instrument and Opto-electronics Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067855146","display_name":"Xuyao Yu","orcid":"https://orcid.org/0000-0001-6831-4039"},"institutions":[{"id":"https://openalex.org/I2802573037","display_name":"Tianjin Medical University Cancer Institute and Hospital","ror":"https://ror.org/0152hn881","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2802573037"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuyao Yu","raw_affiliation_strings":["Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China","institution_ids":["https://openalex.org/I2802573037"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103257788"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":1.2816,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.79913612,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"26","issue":null,"first_page":"1076","last_page":"1081"},"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":0.98089998960495,"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/T14319","display_name":"Currency Recognition and Detection","score":0.972599983215332,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.7205599546432495},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7166615128517151},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6541934609413147},{"id":"https://openalex.org/keywords/epileptic-seizure","display_name":"Epileptic seizure","score":0.6319082379341125},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.611439049243927},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.604676365852356},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.4922453463077545},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.47190243005752563},{"id":"https://openalex.org/keywords/short-time-fourier-transform","display_name":"Short-time Fourier transform","score":0.466716468334198},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.465863972902298},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4517473876476288},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.44781094789505005},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.44225892424583435},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43777328729629517},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.41889631748199463},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.39191925525665283},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2747529447078705},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1841622292995453},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.08430629968643188}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7205599546432495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7166615128517151},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6541934609413147},{"id":"https://openalex.org/C2779334592","wikidata":"https://www.wikidata.org/wiki/Q6279182","display_name":"Epileptic seizure","level":3,"score":0.6319082379341125},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.611439049243927},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.604676365852356},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.4922453463077545},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.47190243005752563},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.466716468334198},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.465863972902298},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4517473876476288},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.44781094789505005},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.44225892424583435},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43777328729629517},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.41889631748199463},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.39191925525665283},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2747529447078705},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1841622292995453},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.08430629968643188},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsai.2017.8248445","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsai.2017.8248445","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 4th International Conference on Systems and Informatics (ICSAI)","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":20,"referenced_works":["https://openalex.org/W89197320","https://openalex.org/W1868744023","https://openalex.org/W1963623761","https://openalex.org/W1997543139","https://openalex.org/W1998559760","https://openalex.org/W2003098244","https://openalex.org/W2008284671","https://openalex.org/W2135202250","https://openalex.org/W2150590430","https://openalex.org/W2155893237","https://openalex.org/W2162480886","https://openalex.org/W2165611870","https://openalex.org/W2322133617","https://openalex.org/W2345242196","https://openalex.org/W2406376216","https://openalex.org/W2421681505","https://openalex.org/W2525929096","https://openalex.org/W2531918295","https://openalex.org/W2557301950","https://openalex.org/W6717632871"],"related_works":["https://openalex.org/W2922348724","https://openalex.org/W200322357","https://openalex.org/W2130428257","https://openalex.org/W2008311543","https://openalex.org/W4308951944","https://openalex.org/W2802845977","https://openalex.org/W4225639054","https://openalex.org/W1967434260","https://openalex.org/W2574021307","https://openalex.org/W2166624857"],"abstract_inverted_index":{"Traditional":[0],"method":[1,33,60,71,88,125],"of":[2,11,19,34,58,72,126,154,163],"epileptic":[3,168],"seizure":[4,36,169],"detection":[5,37],"could":[6,129],"not":[7],"avoid":[8],"the":[9,14,17,35,43,53,56,62,70,79,83,86,90,100,109,117,124,127,131,137,146,158,164,167],"process":[10],"manually":[12],"selecting":[13],"features.":[15],"Recently,":[16],"development":[18],"deep":[20],"learning":[21],"technology":[22],"has":[23,94],"provided":[24],"a":[25,31],"new":[26,32],"direction.":[27],"This":[28],"paper":[29,54,105],"introduces":[30],"based":[38],"on":[39,112],"EEG":[40],"signal":[41],"using":[42,89],"short":[44],"time":[45],"Fourier":[46],"transform(STFT)":[47],"and":[48,66,136,161],"convolution":[49],"neural":[50],"network(CNN).":[51],"And":[52,108],"verifies":[55],"feasibility":[57],"this":[59,104],"through":[61],"actual":[63],"research":[64],"data":[65],"parameter":[67],"setting.":[68],"Afterwards,":[69],"single":[73,113],"threshold":[74],"is":[75,106,115,120],"adopted":[76],"to":[77,134,142,151],"combine":[78],"multi-channel":[80,128],"results.":[81],"Then,":[82],"comparison":[84],"with":[85],"classical":[87],"support":[91],"vector":[92],"machine(SVM)":[93],"been":[95],"done,":[96],"which":[97],"shows":[98],"that":[99,116],"approach":[101,165],"presented":[102],"in":[103],"better.":[107],"experimental":[110],"result":[111],"channel":[114],"average":[118,132,138,147],"accuracy":[119,133],"86%.":[121],"In":[122],"addition,":[123],"increase":[130],"90%":[135],"true":[139],"positive":[140,149],"rate(TPR)":[141],"96.5%":[143],"while":[144],"decrease":[145],"false":[148],"rate(FPR)":[150],"7%.":[152],"All":[153],"those":[155],"indexes":[156],"reveal":[157],"high":[159],"performance":[160],"stability":[162],"for":[166],"detection.":[170]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
