{"id":"https://openalex.org/W4414755921","doi":"https://doi.org/10.32604/cmc.2025.070391","title":"An Efficient CSP-PDW Approach for ECG Signal Compression and Reconstruction for IoT-Based Healthcare","display_name":"An Efficient CSP-PDW Approach for ECG Signal Compression and Reconstruction for IoT-Based Healthcare","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414755921","doi":"https://doi.org/10.32604/cmc.2025.070391"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.070391","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.070391","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.070391","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065498276","display_name":"Hari Mohan","orcid":"https://orcid.org/0000-0003-2557-3510"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hari Mohan Rai","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029086497","display_name":"Chandra Mukherjee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chandra Mukherjee","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010460656","display_name":"Joon Yoo","orcid":"https://orcid.org/0000-0002-9520-5855"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joon Yoo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032710803","display_name":"Hanaa A. Abdallah","orcid":"https://orcid.org/0000-0003-0307-1384"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hanaa A. Abdallah","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089058934","display_name":"Saurabh Agarwal","orcid":"https://orcid.org/0000-0003-3836-2595"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saurabh Agarwal","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5091430134","display_name":"Wooguil Pak","orcid":"https://orcid.org/0000-0002-9551-7373"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wooguil Pak","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5065498276"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.42751543,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"85","issue":"3","first_page":"5723","last_page":"5745"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9656999707221985,"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":0.9656999707221985,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9409999847412109,"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/compressed-sensing","display_name":"Compressed sensing","score":0.6527000069618225},{"id":"https://openalex.org/keywords/signal-reconstruction","display_name":"Signal reconstruction","score":0.6473000049591064},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5770000219345093},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.5360000133514404},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.5314000248908997},{"id":"https://openalex.org/keywords/reconstruction-algorithm","display_name":"Reconstruction algorithm","score":0.5030999779701233},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.45239999890327454},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4465999901294708},{"id":"https://openalex.org/keywords/restricted-isometry-property","display_name":"Restricted isometry property","score":0.4214000105857849}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6527000069618225},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.6473000049591064},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5770000219345093},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5422999858856201},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5360000133514404},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.5314000248908997},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5171999931335449},{"id":"https://openalex.org/C2779898584","wikidata":"https://www.wikidata.org/wiki/Q7820109","display_name":"Reconstruction algorithm","level":3,"score":0.5030999779701233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4675999879837036},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.45239999890327454},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4465999901294708},{"id":"https://openalex.org/C17902559","wikidata":"https://www.wikidata.org/wiki/Q17099734","display_name":"Restricted isometry property","level":3,"score":0.4214000105857849},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4196999967098236},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.41670000553131104},{"id":"https://openalex.org/C2778192920","wikidata":"https://www.wikidata.org/wiki/Q16874989","display_name":"Signal compression","level":4,"score":0.41200000047683716},{"id":"https://openalex.org/C25797200","wikidata":"https://www.wikidata.org/wiki/Q828137","display_name":"Compression ratio","level":3,"score":0.41119998693466187},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3734999895095825},{"id":"https://openalex.org/C2776639384","wikidata":"https://www.wikidata.org/wiki/Q840396","display_name":"Ideal (ethics)","level":2,"score":0.37220001220703125},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3465000092983246},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3409000039100647},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.32010000944137573},{"id":"https://openalex.org/C82457910","wikidata":"https://www.wikidata.org/wiki/Q740207","display_name":"Isometry (Riemannian geometry)","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C94835093","wikidata":"https://www.wikidata.org/wiki/Q3113333","display_name":"Data compression ratio","level":5,"score":0.31290000677108765},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3034000098705292},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.28189998865127563},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.27079999446868896},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C87465248","wikidata":"https://www.wikidata.org/wiki/Q1417790","display_name":"Minimum description length","level":2,"score":0.25859999656677246}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.070391","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.070391","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.070391","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.070391","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2104655872","https://openalex.org/W2108655995","https://openalex.org/W2111414067","https://openalex.org/W2119667497","https://openalex.org/W2154483232","https://openalex.org/W2884238387","https://openalex.org/W4214624336","https://openalex.org/W4226342485","https://openalex.org/W4250955649","https://openalex.org/W4285391271","https://openalex.org/W4313656716","https://openalex.org/W4320712996","https://openalex.org/W4363678159","https://openalex.org/W4367834371","https://openalex.org/W4378512910","https://openalex.org/W4380538682","https://openalex.org/W4385190444","https://openalex.org/W4385431449","https://openalex.org/W4385486275","https://openalex.org/W4386781876","https://openalex.org/W4387054402","https://openalex.org/W4389370889","https://openalex.org/W4398173486"],"related_works":[],"abstract_inverted_index":{"A":[0,58,123],"hybrid":[1],"Compressed":[2],"Sensing":[3],"and":[4,14,21,38,83,93,97,148],"Primal-Dual":[5],"Wavelet":[6],"(CSP-PDW)":[7],"technique":[8],"is":[9,52,65,127],"proposed":[10,63,108],"for":[11,88,115],"the":[12,44,62,70,77,90,95,107,133,145,149,152],"compression":[13,20,46,74,164],"reconstruction":[15,22,48,56],"of":[16,61,73,85,99,106,144,151],"ECG":[17,116,135],"signals.":[18],"The":[19,102,141],"algorithms":[23],"are":[24,155],"implemented":[25],"using":[26,157],"four":[27,158],"key":[28],"concepts:":[29],"Sparsifying":[30],"Basis,":[31],"Restricted":[32],"Isometry":[33],"Principle,":[34],"Gaussian":[35],"Random":[36],"Matrix,":[37],"Convex":[39],"Minimization.":[40],"In":[41],"addition":[42],"to":[43,54,68,130],"conventional":[45],"sensing":[47],"approach,":[49],"wavelet-based":[50],"processing":[51],"employed":[53],"enhance":[55],"efficiency.":[57],"mathematical":[59],"model":[60],"algorithm":[64,109,126,154],"derived":[66],"analytically":[67],"obtain":[69],"essential":[71],"parameters":[72,160],"sensing,":[75],"including":[76],"sparsifying":[78],"basis,":[79],"measurement":[80],"matrix":[81],"size,":[82],"number":[84],"iterations":[86],"required":[87],"reconstructing":[89],"original":[91],"signal":[92,147],"determining":[94],"type":[96],"level":[98],"wavelet":[100],"processing.":[101],"low":[103],"time":[104],"complexity":[105],"makes":[110],"it":[111],"an":[112],"ideal":[113],"candidate":[114],"monitoring":[117],"systems":[118],"in":[119],"IoT-based":[120],"e-healthcare":[121],"applications.":[122],"feature":[124],"extraction":[125],"also":[128],"developed":[129,153],"show":[131],"that":[132],"important":[134],"peaks":[136],"remain":[137],"unaltered":[138],"after":[139],"reconstruction.":[140],"clinical":[142],"relevance":[143],"reconstructed":[146],"efficiency":[150],"evaluated":[156],"validation":[159],"at":[161],"three":[162],"different":[163],"ratios.":[165]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}