{"id":"https://openalex.org/W4412446191","doi":"https://doi.org/10.1109/dsp65409.2025.11074946","title":"Seizure Detection From EEG Signals: Leveraging Poincar\u00e9 Plots with Autoencoder-Classifier Model","display_name":"Seizure Detection From EEG Signals: Leveraging Poincar\u00e9 Plots with Autoencoder-Classifier Model","publication_year":2025,"publication_date":"2025-06-25","ids":{"openalex":"https://openalex.org/W4412446191","doi":"https://doi.org/10.1109/dsp65409.2025.11074946"},"language":"en","primary_location":{"id":"doi:10.1109/dsp65409.2025.11074946","doi":"https://doi.org/10.1109/dsp65409.2025.11074946","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsp65409.2025.11074946","pdf_url":null,"source":{"id":"https://openalex.org/S7407086640","display_name":"IEEE International Conference on Digital Signal Processing (DSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 25th International Conference on Digital Signal Processing (DSP)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5101935055","display_name":"Ritika Jain","orcid":"https://orcid.org/0000-0003-3782-2932","observed_orcids":["https://orcid.org/0000-0003-3782-2932"]},"institutions":[{"id":"https://openalex.org/I4405261081","display_name":"Indian Institute of Technology Madras, Zanzibar","ror":"https://ror.org/04rje7438","country_code":"TZ","type":"education","lineage":["https://openalex.org/I4405261081"]}],"countries":["TZ"],"is_corresponding":true,"raw_author_name":"Ritika Jain","raw_affiliation_strings":["Indian Institute of Technology Madras,Zanzibar,Tanzania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Madras,Zanzibar,Tanzania","institution_ids":["https://openalex.org/I4405261081"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101935055"],"corresponding_institution_ids":["https://openalex.org/I4405261081"],"apc_list":null,"apc_paid":null,"fwci":1.3147,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.75117957,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9994999766349792,"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":0.9994999766349792,"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":9.999999747378752e-05,"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"}},{"id":"https://openalex.org/T10094","display_name":"Epilepsy research and treatment","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Clinical Neurology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/seizure-detection","display_name":"seizure detection","score":0.7979999780654907},{"id":"https://openalex.org/keywords/epileptic-seizures","display_name":"epileptic seizures","score":0.7210000157356262},{"id":"https://openalex.org/keywords/eeg-signals","display_name":"EEG signals","score":0.9010000228881836},{"id":"https://openalex.org/keywords/poincare-plot","display_name":"Poincar\u00e9 plot","score":0.9909999966621399},{"id":"https://openalex.org/keywords/autoencoder","display_name":"autoencoder","score":0.878000020980835},{"id":"https://openalex.org/keywords/latent-representations","display_name":"latent representations","score":0.7990000247955322},{"id":"https://openalex.org/keywords/seizure-classification","display_name":"seizure classification","score":0.5870000123977661},{"id":"https://openalex.org/keywords/seizure-type-classification","display_name":"seizure type classification","score":0.6880000233650208},{"id":"https://openalex.org/keywords/subject-independent-classification","display_name":"subject-independent classification","score":0.8159999847412109}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8592337369918823},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.7169322967529297},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6607611179351807},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5709900259971619},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5633840560913086},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5630133748054504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5542697310447693},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.18795818090438843},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.11984503269195557},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.09666293859481812}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsp65409.2025.11074946","doi":"https://doi.org/10.1109/dsp65409.2025.11074946","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsp65409.2025.11074946","pdf_url":null,"source":{"id":"https://openalex.org/S7407086640","display_name":"IEEE International Conference on Digital Signal Processing (DSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 25th International Conference on Digital Signal Processing (DSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.6240000128746033}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1531344959","https://openalex.org/W1996183177","https://openalex.org/W2053744708","https://openalex.org/W2058508918","https://openalex.org/W2605817454","https://openalex.org/W2783678721","https://openalex.org/W2891590090","https://openalex.org/W2910683885","https://openalex.org/W2945968413","https://openalex.org/W2967087414","https://openalex.org/W3030870789","https://openalex.org/W3164640095","https://openalex.org/W3216927580","https://openalex.org/W4205642372","https://openalex.org/W4280626775","https://openalex.org/W4292862583","https://openalex.org/W4319163863","https://openalex.org/W4362470850","https://openalex.org/W4383426770","https://openalex.org/W4385892652","https://openalex.org/W4389889804","https://openalex.org/W4393406508","https://openalex.org/W4396592210","https://openalex.org/W4400236354","https://openalex.org/W4400391769","https://openalex.org/W4402304190","https://openalex.org/W4405989043"],"related_works":["https://openalex.org/W4411115570","https://openalex.org/W7150173434","https://openalex.org/W4366549304","https://openalex.org/W7203964004","https://openalex.org/W4401000320","https://openalex.org/W4407088859","https://openalex.org/W7163898030","https://openalex.org/W4411409102","https://openalex.org/W4410124751","https://openalex.org/W4200245032"],"abstract_inverted_index":{"Accurate":[0],"detection":[1,100],"of":[2,19,37,53,64,108,130,189,205,208,215,221],"epileptic":[3,141,233],"seizure":[4,20,119,191],"events":[5],"is":[6,76,85,134],"an":[7],"extremely":[8],"challenging":[9],"problem":[10],"due":[11],"to":[12,32,67,136,176],"the":[13,49,104,174,190,194,203,224,240],"complex":[14],"and":[15,56,98,120,140,157,210,232],"highly":[16],"variable":[17],"nature":[18],"activity,":[21],"which":[22,45,91,219],"can":[23,46],"manifest":[24],"differently":[25],"in":[26,106,117,125,153,181,202,229,235,255],"each":[27,107],"individual.":[28],"This":[29,164],"study":[30],"aims":[31],"obtain":[33],"a":[34,69,236],"meaningful":[35],"representation":[36],"EEG":[38,54,196,217],"data":[39],"by":[40],"utilizing":[41],"a)":[42],"Poincar\u00e9":[43],"plots,":[44],"effectively":[47],"capture":[48],"underlying":[50],"temporal":[51],"characteristics":[52],"signal;":[55],"b)":[57],"hybrid":[58],"autoencoder-classifier":[59],"model.":[60],"The":[61,82,95,132],"bottleneck":[62],"layer":[63],"autoencoder":[65],"helps":[66],"provide":[68],"compressed":[70],"latent":[71],"representation,":[72],"while":[73],"classification":[74,165],"head":[75],"used":[77],"for":[78],"accurate":[79],"class":[80],"predictions.":[81],"proposed":[83,241],"approach":[84],"validated":[86],"on":[87,247],"four":[88],"benchmark":[89],"datasets,":[90],"are":[92,246],"publicly":[93],"available.":[94],"mean":[96],"accuracy":[97,152,201,228],"false":[99],"rate":[101],"across":[102,127],"all":[103],"subjects":[105],"these":[109],"datasets":[110],"show":[111],"its":[112],"superior":[113],"performance,":[114],"not":[115],"only":[116],"identifying":[118],"non-seizure":[121],"events,":[122],"but":[123],"also":[124],"distinguishing":[126],"different":[128,187,206],"types":[129,207],"seizures.":[131],"method":[133,242],"able":[135],"distinguish":[137],"healthy":[138,211,231],"controls":[139],"patients":[142],"from":[143,160],"BONN":[144],"dataset":[145,218],"with":[146],"100%":[147],"accuracy.":[148],"It":[149],"provides":[150,199,243],"90%":[151],"classifying":[154,230],"ictal,":[155],"interictal,":[156],"preictal":[158],"segments":[159,234],"New":[161],"Delhi":[162],"dataset.":[163],"task":[166],"becomes":[167],"comparatively":[168],"more":[169],"challenging,":[170],"as":[171],"it":[172,198],"requires":[173],"model":[175,225],"differentiate":[177],"between":[178],"subtle":[179],"variations":[180],"brain":[182],"activity":[183],"that":[184,245],"occur":[185],"during":[186],"phases":[188],"cycle.":[192],"For":[193],"Epileptic":[195],"dataset,":[197],"97%":[200],"identification":[204],"seizures":[209],"data.":[212],"In":[213],"case":[214],"Turkish":[216],"comprises":[220],"121":[222],"subjects,":[223],"achieves":[226],"88%":[227],"subject-independent":[237],"manner.":[238],"Overall,":[239],"results":[244],"par":[248],"with,":[249],"or":[250],"even":[251],"surpass,":[252],"those":[253],"reported":[254],"existing":[256],"works.":[257]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-10-27T15:51:10.671819","created_date":"2025-10-10T00:00:00"}
