{"id":"https://openalex.org/W3015519110","doi":"https://doi.org/10.1109/icassp40776.2020.9054242","title":"Cross-Domain Joint Dictionary Learning for ECG Reconstruction from PPG","display_name":"Cross-Domain Joint Dictionary Learning for ECG Reconstruction from PPG","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015519110","doi":"https://doi.org/10.1109/icassp40776.2020.9054242","mag":"3015519110"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9054242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5069884358","display_name":"Xin Tian","orcid":"https://orcid.org/0000-0003-3984-5505"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xin Tian","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Maryland, College Park, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Maryland, College Park, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060686369","display_name":"Qiang Zhu","orcid":"https://orcid.org/0000-0002-5630-2011"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiang Zhu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Maryland, College Park, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Maryland, College Park, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036663477","display_name":"Yuenan Li","orcid":"https://orcid.org/0000-0001-8932-851X"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuenan Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Maryland, College Park, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Maryland, College Park, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042783680","display_name":"Min Wu","orcid":"https://orcid.org/0000-0001-7672-9357"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Min Wu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Maryland, College Park, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Maryland, College Park, USA","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5069884358"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":1.6464,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.82325277,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"936","last_page":"940"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9998999834060669,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9998999834060669,"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":0.9987999796867371,"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/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/computer-science","display_name":"Computer science","score":0.6984222531318665},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.6507696509361267},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.643672525882721},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5785407423973083},{"id":"https://openalex.org/keywords/photoplethysmogram","display_name":"Photoplethysmogram","score":0.5621856451034546},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5160753130912781},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5077539682388306},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.47207096219062805},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.46064096689224243},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3245600163936615},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17015424370765686},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.13190293312072754},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07645660638809204},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.0742119550704956}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6984222531318665},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.6507696509361267},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.643672525882721},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5785407423973083},{"id":"https://openalex.org/C116390426","wikidata":"https://www.wikidata.org/wiki/Q7187885","display_name":"Photoplethysmogram","level":3,"score":0.5621856451034546},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5160753130912781},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5077539682388306},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.47207096219062805},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.46064096689224243},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3245600163936615},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17015424370765686},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.13190293312072754},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07645660638809204},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0742119550704956},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9054242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5799999833106995,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W976490810","https://openalex.org/W1971373099","https://openalex.org/W2005741801","https://openalex.org/W2010524207","https://openalex.org/W2014933826","https://openalex.org/W2083872334","https://openalex.org/W2086248190","https://openalex.org/W2088254198","https://openalex.org/W2115429828","https://openalex.org/W2120824855","https://openalex.org/W2121058967","https://openalex.org/W2127271355","https://openalex.org/W2128638419","https://openalex.org/W2130187411","https://openalex.org/W2150609919","https://openalex.org/W2160547390","https://openalex.org/W2287095410","https://openalex.org/W2295528320","https://openalex.org/W2396881363","https://openalex.org/W2514534764","https://openalex.org/W2735394685","https://openalex.org/W2788782480","https://openalex.org/W2890527005","https://openalex.org/W2953139536","https://openalex.org/W2972418055","https://openalex.org/W3089282178","https://openalex.org/W6678757208","https://openalex.org/W6767475289"],"related_works":["https://openalex.org/W4297152434","https://openalex.org/W2045049461","https://openalex.org/W1978893398","https://openalex.org/W4381094582","https://openalex.org/W2732360296","https://openalex.org/W1977906818","https://openalex.org/W2201908702","https://openalex.org/W2369625323","https://openalex.org/W2364579609","https://openalex.org/W2600085362"],"abstract_inverted_index":{"An":[0],"emerging":[1],"research":[2],"direction":[3],"considers":[4],"the":[5,18,21,27,48,66,70,81,88,93,107,135,138,141,156],"inverse":[6],"problem":[7],"of":[8,24,31,50,96,99,126,140],"inferring":[9],"electrocardiogram":[10],"(ECG)":[11],"from":[12],"photoplethysmogram":[13],"(PPG)":[14],"to":[15,33,47,64,105],"bring":[16],"about":[17],"synergy":[19],"between":[20,90,109],"easy":[22],"measurability":[23],"PPG":[25,82,152],"and":[26,83,87,129,137],"rich":[28,51],"clinical":[29],"knowledge":[30],"ECG":[32,84,127],"facilitate":[34],"preventive":[35],"healthcare.":[36],"Previous":[37],"reconstruction":[38],"using":[39,151],"a":[40,57,97,103,124],"universal":[41],"basis":[42],"has":[43],"limited":[44],"accuracy":[45,136],"due":[46],"lack":[49],"representative":[52],"power.":[53],"This":[54],"paper":[55],"proposes":[56],"cross-domain":[58,72],"joint":[59,94],"dictionary":[60],"learning":[61,95],"(XDJDL)":[62],"framework":[63],"maximize":[65],"expressive":[67],"power":[68],"for":[69,148],"two":[71],"signals.":[73],"Building":[74],"on":[75,155],"K-SVD":[76],"technique,":[77],"XDJDL":[78],"optimizes":[79],"simultaneously":[80],"signal":[85,100],"representations":[86],"transform":[89,104],"them,":[91],"enabling":[92],"pair":[98],"dictionaries":[101],"with":[102,118],"characterize":[106],"relation":[108],"their":[110],"sparse":[111],"codes.":[112],"The":[113],"proposed":[114,142],"model":[115],"is":[116],"evaluated":[117],"34,000+":[119],"ECG/PPG":[120],"cycle":[121],"pairs":[122],"containing":[123],"variety":[125],"morphologies":[128],"cardiovascular":[130],"diseases.":[131],"Experimental":[132],"results":[133],"validate":[134],"generality":[139],"algorithm,":[143],"suggesting":[144],"an":[145],"encouraging":[146],"potential":[147],"disease":[149],"screening":[150],"measurement":[153],"based":[154],"proactive":[157],"learned":[158],"PPG-ECG":[159],"relationship.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}
