{"id":"https://openalex.org/W2794982513","doi":"https://doi.org/10.22489/cinc.2017.349-105","title":"Automated Detection of Atrial Fbrillation using Fourier-Bessel expansion and Teager Energy Operator from Electrocardiogram Signals","display_name":"Automated Detection of Atrial Fbrillation using Fourier-Bessel expansion and Teager Energy Operator from Electrocardiogram Signals","publication_year":2017,"publication_date":"2017-09-14","ids":{"openalex":"https://openalex.org/W2794982513","doi":"https://doi.org/10.22489/cinc.2017.349-105","mag":"2794982513"},"language":"en","primary_location":{"id":"doi:10.22489/cinc.2017.349-105","is_oa":false,"landing_page_url":"https://doi.org/10.22489/cinc.2017.349-105","pdf_url":null,"source":{"id":"https://openalex.org/S4220650825","display_name":"Computing in cardiology","issn_l":"2325-887X","issn":["2325-887X","2325-8861"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computing in Cardiology Conference (CinC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5064824128","display_name":"Shivnarayan Patidar","orcid":"https://orcid.org/0000-0003-0306-5224"},"institutions":[{"id":"https://openalex.org/I4210109276","display_name":"National Institute of Technology Goa","ror":"https://ror.org/01vmfpj79","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210109276"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shivnarayan Patidar","raw_affiliation_strings":["National Institute of Technology Goa, Ponda, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technology Goa, Ponda, India","institution_ids":["https://openalex.org/I4210109276"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079763100","display_name":"Ashish Sharma","orcid":"https://orcid.org/0000-0002-1011-6504"},"institutions":[{"id":"https://openalex.org/I4210109276","display_name":"National Institute of Technology Goa","ror":"https://ror.org/01vmfpj79","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210109276"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ashish Sharma","raw_affiliation_strings":["National Institute of Technology Goa, Ponda, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technology Goa, Ponda, India","institution_ids":["https://openalex.org/I4210109276"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062563095","display_name":"Niranjan Garg","orcid":null},"institutions":[{"id":"https://openalex.org/I4210089172","display_name":"Midas Multispeciality Hospital","ror":"https://ror.org/009xczs96","country_code":"IN","type":"healthcare","lineage":["https://openalex.org/I4210089172"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Niranjan Garg","raw_affiliation_strings":["Nakshatra Heart and Multispeciality Hospital, Pipliyana Square, Indore, M.P., India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nakshatra Heart and Multispeciality Hospital, Pipliyana Square, Indore, M.P., India","institution_ids":["https://openalex.org/I4210089172"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8744,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.76105362,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9991000294685364,"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/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/energy-operator","display_name":"Energy operator","score":0.741607129573822},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.5243231058120728},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4855341911315918},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.45245370268821716},{"id":"https://openalex.org/keywords/bessel-function","display_name":"Bessel function","score":0.43604785203933716},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.42412033677101135},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4224918484687805},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4060157835483551},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24689438939094543},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09322130680084229},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.0645829439163208}],"concepts":[{"id":"https://openalex.org/C19579662","wikidata":"https://www.wikidata.org/wiki/Q461145","display_name":"Energy operator","level":3,"score":0.741607129573822},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.5243231058120728},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4855341911315918},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.45245370268821716},{"id":"https://openalex.org/C107706756","wikidata":"https://www.wikidata.org/wiki/Q219637","display_name":"Bessel function","level":2,"score":0.43604785203933716},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.42412033677101135},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4224918484687805},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4060157835483551},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24689438939094543},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09322130680084229},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0645829439163208}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.22489/cinc.2017.349-105","is_oa":false,"landing_page_url":"https://doi.org/10.22489/cinc.2017.349-105","pdf_url":null,"source":{"id":"https://openalex.org/S4220650825","display_name":"Computing in cardiology","issn_l":"2325-887X","issn":["2325-887X","2325-8861"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computing in Cardiology Conference (CinC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8700000047683716}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1801984909","https://openalex.org/W1862394037","https://openalex.org/W1944792747","https://openalex.org/W1995875735","https://openalex.org/W2009347435","https://openalex.org/W2026118521","https://openalex.org/W2027774888","https://openalex.org/W2033991357","https://openalex.org/W2057195336","https://openalex.org/W2075415616","https://openalex.org/W2084073756","https://openalex.org/W2099642981","https://openalex.org/W2109692256","https://openalex.org/W2122763650","https://openalex.org/W2123133018","https://openalex.org/W2140005438","https://openalex.org/W2155103273","https://openalex.org/W2167917621","https://openalex.org/W2170605288","https://openalex.org/W2251482333","https://openalex.org/W2338162851","https://openalex.org/W2794550444","https://openalex.org/W2993383518","https://openalex.org/W3188047434"],"related_works":["https://openalex.org/W2033914206","https://openalex.org/W2146076056","https://openalex.org/W2893763841","https://openalex.org/W2163831990","https://openalex.org/W2368779261","https://openalex.org/W3003836766","https://openalex.org/W1775397219","https://openalex.org/W2121440381","https://openalex.org/W2382389115","https://openalex.org/W4205992948"],"abstract_inverted_index":{"This":[0],"work":[1],"presents":[2],"a":[3,36],"new":[4],"method":[5,32],"for":[6,156,197],"detection":[7],"of":[8,38,53,81,106,115,136,152,178,195],"atrial":[9],"fibrillation":[10],"using":[11,82],"predictors":[12,44,55,140],"derived":[13],"from":[14,47,58],"Fourier-Bessel":[15],"(FB)":[16],"expansion":[17,69,84],"and":[18,40,61,66,77,101,108,128,143,181],"Teager":[19],"energy":[20],"operator":[21],"(TEO)":[22],"which":[23],"are":[24,45,56,141,146],"applied":[25,74,119],"strategically":[26],"on":[27,75,120],"electrocardiogram":[28],"(ECG)":[29],"signals.The":[30,79],"proposed":[31],"begins":[33],"by":[34],"extracting":[35],"set":[37],"direct":[39,43],"indirect":[41,54],"predictors.The":[42],"computed":[46,57,142],"pre-processed":[48],"ECG":[49,159],"signals":[50,110],"themselves.A":[51],"part":[52,135],"(a)":[59],"RR-interval":[60],"heart":[62],"rate":[63],"(HR)":[64],"signals,":[65,125],"(b)":[67],"FB":[68,83,98],"along":[70],"with":[71,162,190],"its":[72],"spectrum":[73,103,130],"RR":[76,107],"HR":[78,109,124],"rationale":[80],"is":[85,90,118],"that":[86,105],"the":[87,97,112,133,158,170,174,198],"clinical":[88],"information":[89],"found":[91],"to":[92,131,148],"be":[93],"more":[94],"evident":[95],"in":[96],"coefficients":[99],"(FBC)":[100],"their":[102,129],"than":[104],"themselves.In":[111],"same":[113],"line":[114],"thought,":[116],"TEO":[117],"preprocessed":[121],"ECG,":[122],"RR-interval,":[123],"said":[126],"FBC":[127],"obtain":[132],"other":[134,182],"predictors.In":[137],"all,":[138],"47":[139],"subsequently":[144],"they":[145],"fed":[147],"an":[149],"ensemble":[150],"system":[151],"bagged":[153],"decision":[154],"trees":[155],"classifying":[157],"recordings.When":[160],"evaluated":[161],"2017":[163],"PhysioNet/CinC":[164],"Challenge":[165],"dataset":[166],"(Phase":[167],"II":[168],"subset),":[169],"experimental":[171],"outcomes":[172],"demonstrate":[173],"F":[175,192],"1":[176,193],"scores":[177],"Normal,":[179],"AF":[180],"classes":[183],"as:":[184],"90.89":[185],"%,":[186],"80.07%,":[187],"72.24%":[188],"respectively":[189],"overall":[191],"score":[194],"81%":[196],"hidden":[199],"test":[200],"data.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}