{"id":"https://openalex.org/W2062322691","doi":"https://doi.org/10.1109/bibe.2012.6399691","title":"Exploration of instantaneous amplitude and frequency features for epileptic seizure prediction","display_name":"Exploration of instantaneous amplitude and frequency features for epileptic seizure prediction","publication_year":2012,"publication_date":"2012-11-01","ids":{"openalex":"https://openalex.org/W2062322691","doi":"https://doi.org/10.1109/bibe.2012.6399691","mag":"2062322691"},"language":"en","primary_location":{"id":"doi:10.1109/bibe.2012.6399691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibe.2012.6399691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE)","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/A5100387207","display_name":"Ning Wang","orcid":"https://orcid.org/0000-0003-1410-329X"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ning Wang","raw_affiliation_strings":["Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong","Dept of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"Dept of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069596903","display_name":"Michael R. Lyu","orcid":"https://orcid.org/0000-0002-3666-5798"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Michael R. Lyu","raw_affiliation_strings":["Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong","Dept of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"Dept of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100387207"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":0.9765,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.73618025,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"292","last_page":"297"},"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":0.9984999895095825,"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/T10581","display_name":"Neural dynamics and brain function","score":0.989799976348877,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ictal","display_name":"Ictal","score":0.7570875883102417},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6840451955795288},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6790217757225037},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6495108604431152},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6196209788322449},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6173644065856934},{"id":"https://openalex.org/keywords/epileptic-seizure","display_name":"Epileptic seizure","score":0.6165386438369751},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6066927909851074},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5689940452575684},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.5633636713027954},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5325433611869812},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5271593928337097},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.4958861768245697},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4041751027107239},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.09036999940872192},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.08849078416824341},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07391616702079773}],"concepts":[{"id":"https://openalex.org/C17755696","wikidata":"https://www.wikidata.org/wiki/Q16564780","display_name":"Ictal","level":3,"score":0.7570875883102417},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6840451955795288},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6790217757225037},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6495108604431152},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6196209788322449},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6173644065856934},{"id":"https://openalex.org/C2779334592","wikidata":"https://www.wikidata.org/wiki/Q6279182","display_name":"Epileptic seizure","level":3,"score":0.6165386438369751},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6066927909851074},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5689940452575684},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.5633636713027954},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5325433611869812},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5271593928337097},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.4958861768245697},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4041751027107239},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.09036999940872192},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.08849078416824341},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07391616702079773},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibe.2012.6399691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibe.2012.6399691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1972864710","https://openalex.org/W1978636656","https://openalex.org/W2009902427","https://openalex.org/W2034926081","https://openalex.org/W2047748504","https://openalex.org/W2053744708","https://openalex.org/W2084174584","https://openalex.org/W2086771798","https://openalex.org/W2088222765","https://openalex.org/W2108072369","https://openalex.org/W2114537326","https://openalex.org/W2118981709","https://openalex.org/W2122923860","https://openalex.org/W2127261457","https://openalex.org/W2131442495","https://openalex.org/W2133537872","https://openalex.org/W2138190513","https://openalex.org/W2153635508","https://openalex.org/W2476797758","https://openalex.org/W4309744094","https://openalex.org/W6680455596"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W1820289435","https://openalex.org/W1927135183","https://openalex.org/W1596300871","https://openalex.org/W2890436937","https://openalex.org/W3090190000","https://openalex.org/W1981989525","https://openalex.org/W2331313489","https://openalex.org/W2545382028"],"abstract_inverted_index":{"For":[0],"the":[1,15,38,50,61,97,138,141,166,175,182,196,218,223,232],"purpose":[2],"of":[3,43,140,165,208,217],"effective":[4,158],"epileptic":[5,76,142],"seizure":[6,143],"prediction,":[7,233],"this":[8,107],"paper":[9],"presents":[10],"a":[11,155,237],"new":[12],"representation":[13],"for":[14,137],"electroencephalogram":[16],"(EEG)":[17],"signal":[18,64,153],"by":[19,70,181,192,231],"recurring":[20],"to":[21,37,48,90,131,151,202],"their":[22],"primary":[23],"amplitude":[24,53],"and":[25,40,54,59,66,103,134,210],"frequency":[26,55],"components.":[27],"This":[28],"formulation":[29],"is":[30,111,161,169],"then":[31],"applied":[32],"on":[33,174],"an":[34],"epoch-by-epoch":[35],"basis":[36],"preictal":[39,102],"interictal":[41,104],"states":[42],"EEG":[44,63,177],"signals":[45],"in":[46,81,206,226],"order":[47],"extract":[49],"most":[51,114],"dominant":[52],"characteristics.":[56],"Through":[57],"inspecting":[58],"identifying":[60],"distinctive":[62],"changes":[65],"stage":[67],"transitions":[68],"revealed":[69],"these":[71],"extracted":[72,98],"feature":[73,99,117,198],"vectors,":[74],"upcoming":[75],"seizures":[77,220],"could":[78],"be":[79],"predicted":[80],"due":[82,150],"course.":[83],"Machine":[84],"learning":[85],"approaches":[86],"have":[87,127],"been":[88,190,244],"employed":[89],"construct":[91],"patient-specific":[92],"classifiers":[93],"that":[94,195,236],"can":[95],"divide":[96],"vectors":[100],"into":[101],"groups.":[105],"In":[106,212],"context,":[108],"our":[109,227],"work":[110],"distinguished":[112],"from":[113],"currently":[115],"adopted":[116],"extraction":[118],"process":[119],"which":[120,234],"employs":[121],"time-consuming":[122],"high-dimensional":[123],"parameter":[124],"sets.":[125],"We":[126],"made":[128],"special":[129],"efforts":[130],"derive":[132],"discriminative":[133],"comprehensive":[135],"features":[136],"front-end":[139],"prediction":[144,167,204],"algorithm.":[145],"To":[146],"reduce":[147],"false":[148],"alarms":[149],"trivial":[152],"fluctuation,":[154],"simple":[156],"yet":[157],"post-processing":[159],"step":[160],"incorporated":[162],"thereafter.":[163],"Performance":[164],"algorithm":[168],"assessed":[170],"through":[171],"out-of-sample":[172],"evaluation":[173],"intracranial":[176],"(iEEG)":[178],"recordings":[179],"provided":[180],"publicly":[183],"available":[184],"Freiburg":[185],"data":[186],"set.":[187],"It":[188],"has":[189,243],"shown":[191],"simulation":[193],"results":[194,205],"proposed":[197],"estimation":[199],"method":[200],"leads":[201],"promising":[203],"terms":[207],"sensitivity":[209,238],"specificity.":[211],"particular,":[213],"only":[214],"four":[215],"out":[216],"83":[219],"across":[221],"all":[222],"patients":[224],"included":[225],"experiment":[228],"were":[229],"missed":[230],"means":[235],"as":[239,241],"high":[240],"95.2%":[242],"achieved.":[245]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}