{"id":"https://openalex.org/W2538622217","doi":"https://doi.org/10.1109/fskd.2016.7603383","title":"Improved abnormality detection from raw ECG signals using feature enhancement","display_name":"Improved abnormality detection from raw ECG signals using feature enhancement","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2538622217","doi":"https://doi.org/10.1109/fskd.2016.7603383","mag":"2538622217"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2016.7603383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2016.7603383","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","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/A5023633009","display_name":"Diptangshu Pandit","orcid":"https://orcid.org/0000-0001-7647-3443"},"institutions":[{"id":"https://openalex.org/I32394136","display_name":"Northumbria University","ror":"https://ror.org/049e6bc10","country_code":"GB","type":"education","lineage":["https://openalex.org/I32394136"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Diptangshu Pandit","raw_affiliation_strings":["Computational Intelligence Group, Northumbria university, Newcastle, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computational Intelligence Group, Northumbria university, Newcastle, United Kingdom","institution_ids":["https://openalex.org/I32394136"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418950","display_name":"Li Zhang","orcid":"https://orcid.org/0000-0001-6674-692X"},"institutions":[{"id":"https://openalex.org/I32394136","display_name":"Northumbria University","ror":"https://ror.org/049e6bc10","country_code":"GB","type":"education","lineage":["https://openalex.org/I32394136"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Li Zhang","raw_affiliation_strings":["Computational Intelligence Group, Northumbria university, Newcastle, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computational Intelligence Group, Northumbria university, Newcastle, United Kingdom","institution_ids":["https://openalex.org/I32394136"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041150133","display_name":"Nauman Aslam","orcid":"https://orcid.org/0000-0002-9500-3970"},"institutions":[{"id":"https://openalex.org/I32394136","display_name":"Northumbria University","ror":"https://ror.org/049e6bc10","country_code":"GB","type":"education","lineage":["https://openalex.org/I32394136"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Nauman Aslam","raw_affiliation_strings":["Computational Intelligence Group, Northumbria university, Newcastle, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computational Intelligence Group, Northumbria university, Newcastle, United Kingdom","institution_ids":["https://openalex.org/I32394136"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100764009","display_name":"Changyu Liu","orcid":"https://orcid.org/0000-0002-8185-0191"},"institutions":[{"id":"https://openalex.org/I4210162556","display_name":"Shangri-la Institute","ror":"https://ror.org/05e0fad36","country_code":"CN","type":"nonprofit","lineage":["https://openalex.org/I4210162556"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changyu Liu","raw_affiliation_strings":["Institute of Biomedical Ingineering, Shangdong university, Juan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Biomedical Ingineering, Shangdong university, Juan, China","institution_ids":["https://openalex.org/I4210162556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075720299","display_name":"Samiran Chattopadhyay","orcid":"https://orcid.org/0000-0002-8929-9605"},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Samiran Chattopadhyay","raw_affiliation_strings":["Department of Information Technology, Jadavpur University, Kolkata, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Jadavpur University, Kolkata, India","institution_ids":["https://openalex.org/I170979836"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.75,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.91391583,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1402","last_page":"1406"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9954000115394592,"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory 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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7289737462997437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6941249370574951},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.6702964305877686},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6684225797653198},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6225572824478149},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6114071011543274},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6110048294067383},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5986548066139221},{"id":"https://openalex.org/keywords/abnormality","display_name":"Abnormality","score":0.5448044538497925},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.5027017593383789},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4398387670516968},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4317905604839325},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.4305492341518402},{"id":"https://openalex.org/keywords/beat","display_name":"Beat (acoustics)","score":0.4175727367401123},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3297577500343323}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7289737462997437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6941249370574951},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.6702964305877686},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6684225797653198},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6225572824478149},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6114071011543274},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6110048294067383},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5986548066139221},{"id":"https://openalex.org/C50965678","wikidata":"https://www.wikidata.org/wiki/Q2724302","display_name":"Abnormality","level":2,"score":0.5448044538497925},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.5027017593383789},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4398387670516968},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4317905604839325},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.4305492341518402},{"id":"https://openalex.org/C189809214","wikidata":"https://www.wikidata.org/wiki/Q829522","display_name":"Beat (acoustics)","level":2,"score":0.4175727367401123},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3297577500343323},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/fskd.2016.7603383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2016.7603383","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","raw_type":"proceedings-article"},{"id":"pmh:oai:https://research.tees.ac.uk/ws/oai:openaire_cris_publications/4318bc4c-1705-458a-bb08-38344f76b1a1","is_oa":false,"landing_page_url":"http://www.scopus.com/inward/record.url?scp=84997839810&partnerID=8YFLogxK","pdf_url":null,"source":{"id":"https://openalex.org/S4306401198","display_name":"TeesRep (Teesside University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I874055015","host_organization_name":"Teesside University","host_organization_lineage":["https://openalex.org/I874055015"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Pandit, D, Zhang, L, Aslam, N, Liu, C & Chattopadhyay, S 2016, Improved abnormality detection from raw ECG signals using feature enhancement. in J Du, C Liu, K Li, L Wang, Z Tong, M Li & N Xiong (eds), 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016., 7603383, Institute of Electrical and Electronics Engineers Inc., pp. 1402-1406, 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, Changsha, China, 13/08/16. https://doi.org/10.1109/FSKD.2016.7603383","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:https://research.tees.ac.uk/ws/oai:publications/4318bc4c-1705-458a-bb08-38344f76b1a1","is_oa":false,"landing_page_url":"https://research.tees.ac.uk/en/publications/4318bc4c-1705-458a-bb08-38344f76b1a1","pdf_url":null,"source":{"id":"https://openalex.org/S4306401198","display_name":"TeesRep (Teesside University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I874055015","host_organization_name":"Teesside University","host_organization_lineage":["https://openalex.org/I874055015"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Pandit, D, Zhang, L, Aslam, N, Liu, C & Chattopadhyay, S 2016, Improved abnormality detection from raw ECG signals using feature enhancement. in J Du, C Liu, K Li, L Wang, Z Tong, M Li & N Xiong (eds), 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016., 7603383, Institute of Electrical and Electronics Engineers Inc., pp. 1402-1406, 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, Changsha, China, 13/08/16. https://doi.org/10.1109/FSKD.2016.7603383","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:nrl.northumbria.ac.uk:28847","is_oa":false,"landing_page_url":"http://nrl.northumbria.ac.uk/28847/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401884","display_name":"Northumbria Research Link (Northumbria University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32394136","host_organization_name":"Northumbria University","host_organization_lineage":["https://openalex.org/I32394136"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Book Section"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1548756555","https://openalex.org/W1969433897","https://openalex.org/W1998658041","https://openalex.org/W2008429100","https://openalex.org/W2016927479","https://openalex.org/W2020867940","https://openalex.org/W2033371754","https://openalex.org/W2071901586","https://openalex.org/W2073806155","https://openalex.org/W2080708122","https://openalex.org/W2090916474","https://openalex.org/W2091624809","https://openalex.org/W2095409369","https://openalex.org/W2104330778","https://openalex.org/W2110860969","https://openalex.org/W2142437920","https://openalex.org/W2143730236","https://openalex.org/W2146254945","https://openalex.org/W2162800060","https://openalex.org/W2162893304","https://openalex.org/W2166704538","https://openalex.org/W2207171145","https://openalex.org/W2258033397","https://openalex.org/W2338355707","https://openalex.org/W2370673536","https://openalex.org/W4285719527","https://openalex.org/W6632749939","https://openalex.org/W6688155949","https://openalex.org/W6708275533"],"related_works":["https://openalex.org/W4247543202","https://openalex.org/W4243456421","https://openalex.org/W2417397217","https://openalex.org/W2355857550","https://openalex.org/W3093256375","https://openalex.org/W1841421040","https://openalex.org/W2896815346","https://openalex.org/W3028882978","https://openalex.org/W1487766990","https://openalex.org/W4387382336"],"abstract_inverted_index":{"This":[0],"research":[1],"presents":[2],"an":[3],"abnormal":[4,58],"beat":[5,47,59],"detection":[6],"scheme":[7],"from":[8,107],"lead":[9,104],"II":[10],"Electrocardiogram":[11],"(ECG)":[12],"signals":[13,105],"along":[14,85],"with":[15,86],"some":[16,87],"improvements":[17],"on":[18,101],"feature":[19],"extraction.":[20],"A":[21],"set":[22,124],"of":[23,32,125,143],"16":[24,126],"features":[25,50,127],"representing":[26],"positions,":[27],"durations,":[28],"amplitudes":[29],"and":[30,37,57,81,93,111],"shapes":[31],"P,":[33],"Q,":[34],"R,":[35],"S":[36],"T":[38],"waves":[39],"is":[40],"proposed":[41,99],"in":[42,115],"this":[43,122],"work":[44],"for":[45,55,65,131],"heart":[46],"classification.":[48],"These":[49],"carry":[51],"important":[52],"medical":[53],"information":[54],"normal":[56],"detection.":[60],"Diverse":[61],"classifiers":[62,89],"are":[63],"employed":[64],"abnormality":[66],"detection,":[67],"including":[68],"K-Nearest":[69],"Neighbor,":[70],"Decision":[71],"Tree,":[72],"Artificial":[73],"Neural":[74],"Network,":[75],"Naive":[76],"Bayesian":[77],"Classifier,":[78],"Random":[79],"Forest,":[80],"Support":[82],"Vector":[83],"Machine":[84],"ensemble":[88],"such":[90],"as":[91],"AdaBoostM1":[92],"Bagging.":[94],"We":[95],"have":[96],"evaluated":[97],"the":[98,116,132],"system":[100,139],"raw":[102],"one":[103],"extracted":[106],"MIT-BIH":[108],"Arrhythmia,":[109],"QT":[110],"European":[112],"ST-T":[113],"databases":[114,135],"Physionet":[117],"databank.":[118],"The":[119],"experiments":[120],"using":[121,140],"new":[123],"achieve":[128],"better":[129],"performance":[130],"three":[133],"test":[134],"than":[136],"our":[137],"previous":[138],"a":[141],"subset":[142],"these":[144],"features.":[145]},"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":1},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
