{"id":"https://openalex.org/W3042150822","doi":"https://doi.org/10.1109/memea49120.2020.9137165","title":"A New Method for Dictionary Matrix Optimization in ECG Compressed Sensing","display_name":"A New Method for Dictionary Matrix Optimization in ECG Compressed Sensing","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3042150822","doi":"https://doi.org/10.1109/memea49120.2020.9137165","mag":"3042150822"},"language":"en","primary_location":{"id":"doi:10.1109/memea49120.2020.9137165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea49120.2020.9137165","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","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/A5019883737","display_name":"Enrico Picariello","orcid":"https://orcid.org/0000-0002-0199-6255"},"institutions":[{"id":"https://openalex.org/I16337185","display_name":"University of Sannio","ror":"https://ror.org/04vc81p87","country_code":"IT","type":"education","lineage":["https://openalex.org/I16337185"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Enrico Picariello","raw_affiliation_strings":["Department of Engineering, University of Sannio, Benevento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Engineering, University of Sannio, Benevento, Italy","institution_ids":["https://openalex.org/I16337185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029530605","display_name":"Eulalia Balestrieri","orcid":"https://orcid.org/0000-0002-9155-5989"},"institutions":[{"id":"https://openalex.org/I16337185","display_name":"University of Sannio","ror":"https://ror.org/04vc81p87","country_code":"IT","type":"education","lineage":["https://openalex.org/I16337185"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Eulalia Balestrieri","raw_affiliation_strings":["Department of Engineering, University of Sannio, Benevento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Engineering, University of Sannio, Benevento, Italy","institution_ids":["https://openalex.org/I16337185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087692673","display_name":"Francesco Picariello","orcid":"https://orcid.org/0000-0001-6854-3026"},"institutions":[{"id":"https://openalex.org/I16337185","display_name":"University of Sannio","ror":"https://ror.org/04vc81p87","country_code":"IT","type":"education","lineage":["https://openalex.org/I16337185"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesco Picariello","raw_affiliation_strings":["Department of Engineering, University of Sannio, Benevento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Engineering, University of Sannio, Benevento, Italy","institution_ids":["https://openalex.org/I16337185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010415569","display_name":"Sergio Rapuano","orcid":"https://orcid.org/0000-0003-3249-0473"},"institutions":[{"id":"https://openalex.org/I16337185","display_name":"University of Sannio","ror":"https://ror.org/04vc81p87","country_code":"IT","type":"education","lineage":["https://openalex.org/I16337185"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Sergio Rapuano","raw_affiliation_strings":["Department of Engineering, University of Sannio, Benevento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Engineering, University of Sannio, Benevento, Italy","institution_ids":["https://openalex.org/I16337185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087673689","display_name":"Ioan Tudosa","orcid":"https://orcid.org/0000-0002-5127-578X"},"institutions":[{"id":"https://openalex.org/I16337185","display_name":"University of Sannio","ror":"https://ror.org/04vc81p87","country_code":"IT","type":"education","lineage":["https://openalex.org/I16337185"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Ioan Tudosa","raw_affiliation_strings":["Department of Engineering, University of Sannio, Benevento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Engineering, University of Sannio, Benevento, Italy","institution_ids":["https://openalex.org/I16337185"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074293414","display_name":"Luca De Vito","orcid":"https://orcid.org/0000-0003-1896-2614"},"institutions":[{"id":"https://openalex.org/I16337185","display_name":"University of Sannio","ror":"https://ror.org/04vc81p87","country_code":"IT","type":"education","lineage":["https://openalex.org/I16337185"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luca De Vito","raw_affiliation_strings":["Department of Engineering, University of Sannio, Benevento, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Engineering, University of Sannio, Benevento, Italy","institution_ids":["https://openalex.org/I16337185"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5019883737"],"corresponding_institution_ids":["https://openalex.org/I16337185"],"apc_list":null,"apc_paid":null,"fwci":1.5845,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.8055076,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9980000257492065,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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":0.7209368944168091},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.6359966397285461},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.5243616104125977},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4657749831676483},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3787018656730652},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3432697355747223},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.09016510844230652}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7209368944168091},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6359966397285461},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.5243616104125977},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4657749831676483},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3787018656730652},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3432697355747223},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.09016510844230652},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/memea49120.2020.9137165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea49120.2020.9137165","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W106636645","https://openalex.org/W1554336774","https://openalex.org/W1970021615","https://openalex.org/W1974198688","https://openalex.org/W1995756791","https://openalex.org/W2010982913","https://openalex.org/W2065321782","https://openalex.org/W2119667497","https://openalex.org/W2155321485","https://openalex.org/W2162409952","https://openalex.org/W2164696938","https://openalex.org/W2169382889","https://openalex.org/W2171195459","https://openalex.org/W2186267338","https://openalex.org/W2287095410","https://openalex.org/W2611593115","https://openalex.org/W2774282787","https://openalex.org/W2783768118","https://openalex.org/W2786561765","https://openalex.org/W2801751791","https://openalex.org/W2884996318","https://openalex.org/W2890557292","https://openalex.org/W2910605105","https://openalex.org/W2912476690","https://openalex.org/W2955070708","https://openalex.org/W2967832933","https://openalex.org/W3011856620","https://openalex.org/W4250955649","https://openalex.org/W6632961610"],"related_works":["https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W3011821305","https://openalex.org/W2737338842","https://openalex.org/W3005946484","https://openalex.org/W4387560237","https://openalex.org/W4285148873","https://openalex.org/W2045476623","https://openalex.org/W4287713161","https://openalex.org/W2076468490"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,23,67,71,74,109,125,138],"new":[4],"method":[5,29,123,139],"for":[6,98],"dictionary":[7,50,104,143],"matrix":[8],"optimization":[9,105],"with":[10,51,73],"the":[11,15,31,36,39,43,57,61,81,88,92,99,121,141],"aim":[12],"of":[13,18,38,42,91,130,132],"improving":[14],"reconstruction":[16,59,83,93,126],"quality":[17,84,127],"ECG":[19,40,102],"signals":[20,103],"delivered":[21],"by":[22,70],"Compressed":[24],"Sensing":[25],"(CS)":[26],"algorithm.":[27,94],"The":[28,95,115],"exploits":[30],"features":[32],"common":[33],"to":[34,46,79,86],"all":[35],"records":[37],"signal":[41,58],"same":[44],"patient":[45,100],"obtain":[47],"an":[48],"optimized":[49],"reduced":[52,75],"size.":[53],"In":[54],"this":[55],"way,":[56],"from":[60],"compressed":[62],"samples":[63],"is":[64,106,113],"performed":[65],"in":[66,128],"do-main":[68],"defined":[69],"base":[72],"cardinality,":[76],"thus":[77],"allowing":[78],"increase":[80],"signal\u2019s":[82],"and":[85,108],"reduce":[87],"execution":[89],"time":[90],"mathematical":[96],"model":[97],"specific":[101],"described,":[107],"preliminary":[110],"experimental":[111],"assessment":[112],"presented.":[114],"obtained":[116],"results":[117],"clearly":[118],"demonstrates":[119],"that":[120],"proposed":[122],"exhibits":[124],"terms":[129],"Percentage":[131],"Root-mean-squared":[133],"Difference":[134],"(PRD)":[135],"lower":[136],"than":[137],"adopting":[140],"non-optimized":[142],"matrix.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
