{"id":"https://openalex.org/W2290022144","doi":"https://doi.org/10.1109/bmei.2015.7401499","title":"ECG signal compressed sensing using the wavelet tree model","display_name":"ECG signal compressed sensing using the wavelet tree model","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2290022144","doi":"https://doi.org/10.1109/bmei.2015.7401499","mag":"2290022144"},"language":"en","primary_location":{"id":"doi:10.1109/bmei.2015.7401499","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmei.2015.7401499","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 8th International Conference on Biomedical Engineering and Informatics (BMEI)","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/A5100622225","display_name":"Zhicheng Li","orcid":"https://orcid.org/0000-0003-4140-0580"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhicheng Li","raw_affiliation_strings":["Harbin Institute of Technology Harbin, Heilongjiang, China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology Harbin, Heilongjiang, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101627282","display_name":"Yang Deng","orcid":"https://orcid.org/0000-0002-7318-1899"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Deng","raw_affiliation_strings":["Harbin Institute of Technology Harbin, Heilongjiang, China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology Harbin, Heilongjiang, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041368835","display_name":"Hongbin Huang","orcid":"https://orcid.org/0000-0002-5179-3640"},"institutions":[{"id":"https://openalex.org/I10052268","display_name":"New Mexico State University","ror":"https://ror.org/00hpz7z43","country_code":"US","type":"education","lineage":["https://openalex.org/I10052268"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hong Huang","raw_affiliation_strings":["Klipsch School of Electrical & Computer Engineering, New Mexico State University, NM, USA"],"affiliations":[{"raw_affiliation_string":"Klipsch School of Electrical & Computer Engineering, New Mexico State University, NM, USA","institution_ids":["https://openalex.org/I10052268"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029387062","display_name":"Satyajayant Misra","orcid":"https://orcid.org/0000-0001-7347-984X"},"institutions":[{"id":"https://openalex.org/I10052268","display_name":"New Mexico State University","ror":"https://ror.org/00hpz7z43","country_code":"US","type":"education","lineage":["https://openalex.org/I10052268"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Satyajayant Misra","raw_affiliation_strings":["Department of Computer Science, New Mexico State University, NM, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, New Mexico State University, NM, USA","institution_ids":["https://openalex.org/I10052268"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100622225"],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":0.3813,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.64480589,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"194","last_page":"199"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10323","display_name":"Analog and Mixed-Signal Circuit Design","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10323","display_name":"Analog and Mixed-Signal Circuit Design","score":0.9994999766349792,"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"}},{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9994999766349792,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994000196456909,"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/wavelet","display_name":"Wavelet","score":0.7925708889961243},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5796160697937012},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5468721389770508},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5447347164154053},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5286213159561157},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5237479209899902},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.49581727385520935},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.48277202248573303},{"id":"https://openalex.org/keywords/daubechies-wavelet","display_name":"Daubechies wavelet","score":0.4732666015625},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.4697575569152832},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.4679488241672516},{"id":"https://openalex.org/keywords/nyquist-rate","display_name":"Nyquist rate","score":0.4665061831474304},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4604213237762451},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4280456602573395},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.411723792552948},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4083724021911621},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.40735089778900146},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.2978007197380066},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.26339343190193176},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.13046589493751526},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.07951465249061584},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07053270936012268}],"concepts":[{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.7925708889961243},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5796160697937012},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5468721389770508},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5447347164154053},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5286213159561157},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5237479209899902},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.49581727385520935},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.48277202248573303},{"id":"https://openalex.org/C2779855323","wikidata":"https://www.wikidata.org/wiki/Q1172774","display_name":"Daubechies wavelet","level":5,"score":0.4732666015625},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.4697575569152832},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.4679488241672516},{"id":"https://openalex.org/C65914096","wikidata":"https://www.wikidata.org/wiki/Q6273772","display_name":"Nyquist rate","level":4,"score":0.4665061831474304},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4604213237762451},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4280456602573395},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.411723792552948},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4083724021911621},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.40735089778900146},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2978007197380066},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.26339343190193176},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.13046589493751526},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.07951465249061584},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07053270936012268},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bmei.2015.7401499","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmei.2015.7401499","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 8th International Conference on Biomedical Engineering and Informatics (BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1985475042","https://openalex.org/W1991724591","https://openalex.org/W1995756791","https://openalex.org/W2043099284","https://openalex.org/W2095409369","https://openalex.org/W2104266187","https://openalex.org/W2106759147","https://openalex.org/W2115755118","https://openalex.org/W2125680629","https://openalex.org/W2130084903","https://openalex.org/W2137611399","https://openalex.org/W2146131752","https://openalex.org/W2163916252","https://openalex.org/W2164452299","https://openalex.org/W2166152820","https://openalex.org/W2296616510","https://openalex.org/W3125735862","https://openalex.org/W4250955649","https://openalex.org/W6680658823"],"related_works":["https://openalex.org/W2356275480","https://openalex.org/W2786561765","https://openalex.org/W2899148860","https://openalex.org/W4234932947","https://openalex.org/W2793783688","https://openalex.org/W2115504648","https://openalex.org/W2468414543","https://openalex.org/W2159420092","https://openalex.org/W2294732742","https://openalex.org/W2295430099"],"abstract_inverted_index":{"Compressed":[0],"Sensing":[1],"(CS)":[2],"is":[3,73,81,116,130],"a":[4,12,54],"novel":[5],"approach":[6,72],"of":[7,19,45,75,94,188],"compressing,":[8],"which":[9],"can":[10,24],"reconstruct":[11,59],"sparse":[13,102],"signal":[14,47],"much":[15],"below":[16],"Nyquist":[17],"rate":[18],"sampling.":[20],"Though":[21],"ECG":[22,37,60,98,109],"signals":[23,61,99,103],"be":[25],"well":[26],"approximated":[27],"by":[28,132,162],"some":[29,133],"wavelet":[30,38,69,173,184],"basis,":[31],"the":[32,36,43,46,92,95,113],"noise":[33,96],"still":[34],"influences":[35],"decomposition":[39],"and":[40,86,100,106,111,123,152,171,186],"also":[41],"reduces":[42],"effectiveness":[44],"reconstruction.":[48],"In":[49],"this":[50],"note,":[51],"we":[52],"present":[53],"compressed":[55],"sensing":[56],"method":[57,120],"to":[58,82,90,104,117,121,182],"in":[62],"MITBIH":[63],"[1]":[64],"arrhythmia":[65],"based":[66],"on":[67],"different":[68],"families.":[70],"Our":[71],"composed":[74],"two":[76],"steps.":[77],"The":[78,128],"first":[79],"step":[80,115],"use":[83,118],"Condensing":[84],"Sort":[85],"Select":[87],"Algorithm":[88],"(CSSA)":[89],"dampen":[91],"impact":[93],"for":[97,178],"get":[101],"estimate":[105],"replace":[107],"raw":[108],"signals,":[110],"then,":[112],"second":[114],"CS":[119],"compress":[122],"transfer":[124],"those":[125],"filtered":[126],"signals.":[127],"result":[129],"evaluated":[131],"indices":[134],"like":[135],"Percentage":[136],"Root":[137],"Mean":[138,142],"Square":[139,143],"Difference":[140],"(PRD),":[141],"Error":[144],"(MSE),":[145],"Peak":[146],"Signal":[147],"To":[148],"Noise":[149],"Ratio":[150],"(PSNR),":[151],"Correlation":[153],"Coefficient":[154],"(CoC).":[155],"These":[156,166],"reconstructed":[157],"results":[158,167],"are":[159],"comprehensively":[160],"compared":[161,181],"4:1":[163],"compression":[164],"ratio.":[165],"indicate":[168],"that":[169],"Symlets":[170],"Daubechies":[172],"families":[174,185],"have":[175],"better":[176],"performance":[177],"all":[179],"parameters":[180],"other":[183],"most":[187],"existing":[189],"results.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
