{"id":"https://openalex.org/W2993358495","doi":"https://doi.org/10.1109/tencon.2019.8929571","title":"Modified sparse representation for ECG reconstruction in telemonitoring","display_name":"Modified sparse representation for ECG reconstruction in telemonitoring","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2993358495","doi":"https://doi.org/10.1109/tencon.2019.8929571","mag":"2993358495"},"language":"en","primary_location":{"id":"doi:10.1109/tencon.2019.8929571","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2019.8929571","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON)","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/A5059011224","display_name":"Sushree Satvatee Swain","orcid":"https://orcid.org/0000-0001-9515-9572"},"institutions":[{"id":"https://openalex.org/I16292982","display_name":"National Institute of Technology Rourkela","ror":"https://ror.org/011gmn932","country_code":"IN","type":"education","lineage":["https://openalex.org/I16292982"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Sushree Satvatee Swain","raw_affiliation_strings":["Department of Electrical Engineering, National Institute of Technology, Rourkela, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Institute of Technology, Rourkela, India","institution_ids":["https://openalex.org/I16292982"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037743544","display_name":"Dipti Patra","orcid":"https://orcid.org/0000-0002-6094-3735"},"institutions":[{"id":"https://openalex.org/I16292982","display_name":"National Institute of Technology Rourkela","ror":"https://ror.org/011gmn932","country_code":"IN","type":"education","lineage":["https://openalex.org/I16292982"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Dipti Patra","raw_affiliation_strings":["Department of Electrical Engineering, National Institute of Technology, Rourkela, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Institute of Technology, Rourkela, India","institution_ids":["https://openalex.org/I16292982"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5059011224"],"corresponding_institution_ids":["https://openalex.org/I16292982"],"apc_list":null,"apc_paid":null,"fwci":0.1603,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.58408798,"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":"1926","last_page":"1931"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9997000098228455,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7620807886123657},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6724663972854614},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.6661823391914368},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5852583646774292},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5687156915664673},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.5486248135566711},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.532961905002594},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5143483877182007},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5096850395202637},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5081877708435059},{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.5068781971931458},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41593918204307556},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.3645530939102173},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06711483001708984}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7620807886123657},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6724663972854614},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.6661823391914368},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5852583646774292},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5687156915664673},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5486248135566711},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.532961905002594},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5143483877182007},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5096850395202637},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5081877708435059},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.5068781971931458},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41593918204307556},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3645530939102173},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06711483001708984},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon.2019.8929571","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon.2019.8929571","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1591116419","https://openalex.org/W2010755794","https://openalex.org/W2018328737","https://openalex.org/W2034694726","https://openalex.org/W2044023093","https://openalex.org/W2047922146","https://openalex.org/W2065506507","https://openalex.org/W2067731315","https://openalex.org/W2110075977","https://openalex.org/W2114122776","https://openalex.org/W2115340664","https://openalex.org/W2121396509","https://openalex.org/W2133900413","https://openalex.org/W2152328854","https://openalex.org/W2153663612","https://openalex.org/W2160547390","https://openalex.org/W2164142411","https://openalex.org/W2168538279","https://openalex.org/W2296616510","https://openalex.org/W2536065119","https://openalex.org/W2585015296","https://openalex.org/W4235713725","https://openalex.org/W4250955649","https://openalex.org/W4298729467"],"related_works":["https://openalex.org/W2378166785","https://openalex.org/W2156466545","https://openalex.org/W2379468505","https://openalex.org/W3104324607","https://openalex.org/W4206981968","https://openalex.org/W1987102304","https://openalex.org/W2308961925","https://openalex.org/W2601968125","https://openalex.org/W4285251805","https://openalex.org/W2102910599"],"abstract_inverted_index":{"Presently":[0],"ECG":[1,42,52,64,103,131,168,191],"signal":[2,148,192],"telemonitoring":[3,22],"is":[4,15,125],"one":[5],"of":[6,32,40,56,62,72,189],"the":[7,50,74,101,129,143,147,173,181,187,190],"essential":[8],"branch":[9],"in":[10,80,96,146],"telemedicine":[11],"system.":[12],"So":[13],"it":[14],"highly":[16],"desirable":[17],"to":[18,48,99,127,151,165],"construct":[19],"a":[20],"robust":[21],"system":[23],"through":[24],"wireless":[25],"body":[26],"area":[27],"network":[28],"(WBAN)":[29],"with":[30,118,133],"consumption":[31],"less":[33,36],"energy":[34],"and":[35,60,69,136,149],"power.":[37],"A":[38],"number":[39],"traditional":[41,75,182],"reconstruction":[43,88,113,178],"techniques":[44],"have":[45],"been":[46],"proposed":[47,106,174],"recover":[49,166],"clean":[51,102],"data.":[53,104],"However":[54],"because":[55],"some":[57],"specific":[58],"behavior":[59],"characteristics":[61],"raw":[63,130,167],"data":[65],"like":[66],"non":[67],"sparsity":[68,188],"heavy":[70],"contamination":[71],"noise":[73],"methods":[76],"do":[77],"not":[78],"succeed":[79],"this":[81,123,171],"application.":[82],"This":[83],"paper":[84],"proposes":[85],"an":[86,97],"effective":[87],"method":[89,175,185],"followed":[90],"by":[91],"Independent":[92],"Component":[93],"Analysis":[94],"(ICA)":[95],"intention":[98],"obtain":[100],"The":[105],"framework":[107,124],"includes":[108],"context":[109,145],"based":[110,140],"learning":[111,141],"adopted":[112],"method.":[114],"Experimental":[115],"results":[116,120],"along":[117],"simulation":[119],"show":[121],"that":[122],"able":[126],"reconstruct":[128],"recordings":[132],"high":[134,137],"accuracy":[135],"quality.":[138],"Context":[139],"learns":[142],"existing":[144],"reacts":[150],"changing":[152],"context,":[153],"which":[154],"uses":[155],"k-means":[156],"clustering":[157],"via":[158],"singular":[159],"value":[160],"decomposition":[161],"i.e.":[162],"KSVD":[163],"algorithm":[164],"signal.":[169],"In":[170],"paper,":[172],"shows":[176],"better":[177],"performance":[179],"than":[180],"compressed":[183],"sensing":[184],"retaining":[186],"intact.":[193]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}