Exploiting Prior Knowledge in Compressed Sensing Wireless ECG Systems
Recent results in telecardiology show that compressed sensing (CS) is a promising tool to lower energy consumption in wireless body area networks for electrocardiogram (ECG) monitoring. However, the performance of current CS-based algorithms, in terms of compression rate and reconstruction quality o...
Saved in:
Published in | IEEE journal of biomedical and health informatics Vol. 19; no. 2; pp. 508 - 519 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
United States
IEEE
01.03.2015
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | Recent results in telecardiology show that compressed sensing (CS) is a promising tool to lower energy consumption in wireless body area networks for electrocardiogram (ECG) monitoring. However, the performance of current CS-based algorithms, in terms of compression rate and reconstruction quality of the ECG, still falls short of the performance attained by state-of-the-art wavelet-based algorithms. In this paper, we propose to exploit the structure of the wavelet representation of the ECG signal to boost the performance of CS-based methods for compression and reconstruction of ECG signals. More precisely, we incorporate prior information about the wavelet dependencies across scales into the reconstruction algorithms and exploit the high fraction of common support of the wavelet coefficients of consecutive ECG segments. Experimental results utilizing the MIT-BIH Arrhythmia Database show that significant performance gains, in terms of compression rate and reconstruction quality, can be obtained by the proposed algorithms compared to current CS-based methods. |
---|---|
AbstractList | Recent results in telecardiology show that compressed sensing (CS) is a promising tool to lower energy consumption in wireless body area networks for electrocardiogram (ECG) monitoring. However, the performance of current CS-based algorithms, in terms of compression rate and reconstruction quality of the ECG, still falls short of the performance attained by state-of-the-art wavelet-based algorithms. In this paper, we propose to exploit the structure of the wavelet representation of the ECG signal to boost the performance of CS-based methods for compression and reconstruction of ECG signals. More precisely, we incorporate prior information about the wavelet dependencies across scales into the reconstruction algorithms and exploit the high fraction of common support of the wavelet coefficients of consecutive ECG segments. Experimental results utilizing the MIT-BIH Arrhythmia Database show that significant performance gains, in terms of compression rate and reconstruction quality, can be obtained by the proposed algorithms compared to current CS-based methods. |
Author | Carrillo, Rafael E. Blanco-Velasco, Manuel Barner, Kenneth E. Polania, Luisa F. |
Author_xml | – sequence: 1 givenname: Luisa F. surname: Polania fullname: Polania, Luisa F. email: lfpolani@udel.edu organization: Dept. of Electr. & Comput. Eng., Univ. of Delaware, Newark, DE, USA – sequence: 2 givenname: Rafael E. surname: Carrillo fullname: Carrillo, Rafael E. email: rafael.carrillo@epfl.ch organization: Inst. of Electr. Eng., Ecole Polytech. Fed. de Lausanne (EPFL), Lausanne, Switzerland – sequence: 3 givenname: Manuel surname: Blanco-Velasco fullname: Blanco-Velasco, Manuel email: manuel.blanco@uah.es organization: Dept. of Signal Theor. & Commun., Univ. de Alcala, Alcala de Henares, Spain – sequence: 4 givenname: Kenneth E. surname: Barner fullname: Barner, Kenneth E. email: barner@udel.edu organization: Dept. of Electr. & Comput. Eng., Univ. of Delaware, Newark, DE, USA |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24846672$$D View this record in MEDLINE/PubMed |
BookMark | eNo9kE1Lw0AQhhepWK39ASJIjl5Sdzafe9QQ22pBoYrHsMlOykq-3E3R_ns39GMuM8w87xyeKzJq2gYJuQE6A6D84eVpsZwxCv6MeSygEJ2RSwZh7DJG49FxBu6PydSYb2ortiseXpAx82M_DCN2SdL0r6ta1atm47xr1WrntWl_K5QbdFTjJG3daTQGpbPGxgzUl9JY2ZWTJnNnvTM91uaanJeiMjg99An5fE4_koW7epsvk8eVW3gMerfkAeOClggSpIQCpRASWBEDFIJDWEZC5kVeUAkB8z2PxxJyWZbCds5QehNyv__b6fZni6bPamUKrCrRYLs1GYShzYE1YFHYo4VujdFYZp1WtdC7DGg2CMwGgdkgMDsItJm7w_ttXqM8JY66LHC7BxQins5hDFHgMe8fcYZ2aw |
CODEN | IJBHA9 |
CitedBy_id | crossref_primary_10_1109_JBHI_2016_2531182 crossref_primary_10_1109_JBHI_2024_3352927 crossref_primary_10_1016_j_bspc_2021_103065 crossref_primary_10_1016_j_bspc_2020_102047 crossref_primary_10_1016_j_dsp_2020_102862 crossref_primary_10_1049_htl_2015_0011 crossref_primary_10_1080_03772063_2021_2012281 crossref_primary_10_1007_s00034_020_01483_x crossref_primary_10_1016_j_bspc_2018_08_016 crossref_primary_10_1515_jisys_2019_0215 crossref_primary_10_1016_j_compbiomed_2016_01_013 crossref_primary_10_1016_j_bspc_2021_102768 crossref_primary_10_1016_j_future_2022_12_012 crossref_primary_10_1016_j_compbiomed_2016_03_021 crossref_primary_10_1016_j_compbiomed_2017_03_023 crossref_primary_10_1108_IJPCC_08_2019_0065 crossref_primary_10_3390_diagnostics8010010 crossref_primary_10_1109_TBCAS_2018_2828031 crossref_primary_10_1109_JBHI_2018_2817192 crossref_primary_10_1016_j_bspc_2020_101960 crossref_primary_10_1016_j_bspc_2018_05_022 crossref_primary_10_1049_iet_smt_2016_0360 crossref_primary_10_1080_03772063_2018_1507765 crossref_primary_10_3390_s20061796 crossref_primary_10_4015_S1016237219500224 crossref_primary_10_1016_j_bspc_2018_10_005 crossref_primary_10_1109_JBHI_2021_3128169 crossref_primary_10_1007_s12065_016_0139_0 crossref_primary_10_1038_s41598_017_00540_x crossref_primary_10_1088_1361_6579_ac9214 crossref_primary_10_1016_j_cmpb_2021_106358 crossref_primary_10_1016_j_bspc_2019_101685 crossref_primary_10_1007_s40012_019_00242_x crossref_primary_10_1109_JSEN_2021_3055635 crossref_primary_10_1007_s11277_017_5079_1 crossref_primary_10_3390_s21092969 crossref_primary_10_1016_j_bspc_2021_102786 crossref_primary_10_1109_TBCAS_2018_2879818 crossref_primary_10_1155_2017_9823684 crossref_primary_10_1016_j_bspc_2018_12_019 crossref_primary_10_1049_htl_2016_0049 crossref_primary_10_3390_s20020373 crossref_primary_10_1109_ACCESS_2022_3149890 crossref_primary_10_1016_j_bspc_2019_101593 crossref_primary_10_1016_j_compeleceng_2016_01_027 crossref_primary_10_1109_JIOT_2020_3015237 crossref_primary_10_1007_s10916_016_0526_1 crossref_primary_10_1007_s11042_022_13444_4 crossref_primary_10_1016_j_bspc_2018_05_005 crossref_primary_10_1080_23080477_2023_2258643 crossref_primary_10_1038_s41598_019_40350_x crossref_primary_10_1049_iet_spr_2018_5076 crossref_primary_10_1109_TBCAS_2020_2982824 crossref_primary_10_4015_S1016237221500344 crossref_primary_10_1016_j_bspc_2016_05_008 crossref_primary_10_1109_TBME_2016_2631620 crossref_primary_10_1109_TIM_2018_2811438 crossref_primary_10_1016_j_bspc_2021_102773 crossref_primary_10_1109_JSEN_2022_3190207 crossref_primary_10_1007_s00542_016_3240_5 crossref_primary_10_1016_j_hcc_2023_100125 crossref_primary_10_1371_journal_pone_0262219 crossref_primary_10_3390_s18072021 |
Cites_doi | 10.1109/TIT.2007.909108 10.1161/01.CIR.101.23.e215 10.1109/4233.924801 10.1137/060657704 10.1109/10.846678 10.1109/MSP.2007.914731 10.1109/NEBC.2012.6207081 10.1137/S1064827596304010 10.1007/978-1-4615-3626-0 10.1023/A:1014554317692 10.1016/j.acha.2008.07.002 10.1137/090772447 10.1109/TBCAS.2012.2193668 10.1109/TIT.2010.2040894 10.1109/ICASSP.2010.5495901 10.1016/j.acha.2009.04.002 10.1117/12.919478 10.1109/10.568915 10.1109/DSP-SPE.2013.6642561 10.1007/s10208-008-9031-3 10.1109/TITB.2005.854512 10.1109/TBME.2012.2226175 10.1109/ICASSP.2011.5946515 10.1016/j.ipl.2008.09.028 10.1109/JETCAS.2012.2220253 10.1109/TSP.2010.2051150 10.1109/MCOM.2009.5350373 10.1109/78.668544 10.1109/BioCAS.2011.6107743 10.1109/TIT.2006.871582 10.1109/TBME.2008.918465 10.1109/JSSC.2011.2179451 10.1109/TBME.2011.2156795 |
ContentType | Journal Article |
DBID | 97E RIA RIE CGR CUY CVF ECM EIF NPM AAYXX CITATION 7X8 |
DOI | 10.1109/JBHI.2014.2325017 |
DatabaseName | IEEE All-Society Periodicals Package (ASPP) 2005-present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE/IET Electronic Library (IEL) Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed CrossRef MEDLINE - Academic |
DatabaseTitle | MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) CrossRef MEDLINE - Academic |
DatabaseTitleList | MEDLINE - Academic MEDLINE |
Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database – sequence: 3 dbid: RIE name: IEEE/IET Electronic Library (IEL) url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/ sourceTypes: Publisher |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Medicine |
EISSN | 2168-2208 |
EndPage | 519 |
ExternalDocumentID | 10_1109_JBHI_2014_2325017 24846672 6817532 |
Genre | orig-research Journal Article |
GroupedDBID | 0R~ 4.4 6IF 6IH 6IK 6IL 97E AAJGR AASAJ ABQJQ ABVLG ACIWK ACPRK ADZIZ AENEX AFRAH AKJIK ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ CHZPO EBS EJD HZ~ IFIPE IPLJI JAVBF M43 O9- OCL PQQKQ RIA RIE RIG RNS CGR CUY CVF ECM EIF NPM AAYXX CITATION 7X8 |
ID | FETCH-LOGICAL-c321t-f9529a0fe1d1dd1cedaad12c811ca916f7adbcbc0d15243398d1bdffa8d192ed3 |
IEDL.DBID | RIE |
ISSN | 2168-2194 |
IngestDate | Wed Jul 24 15:49:04 EDT 2024 Fri Aug 23 02:45:41 EDT 2024 Sat Sep 28 07:53:52 EDT 2024 Wed Jun 26 19:22:05 EDT 2024 |
IsDoiOpenAccess | false |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 2 |
Keywords | electrocardiogram (ECG) compressed sensing (CS) wireless body area networks (WBAN) wavelet transform |
Language | English |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c321t-f9529a0fe1d1dd1cedaad12c811ca916f7adbcbc0d15243398d1bdffa8d192ed3 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
PMID | 24846672 |
PQID | 1662431220 |
PQPubID | 23479 |
PageCount | 12 |
ParticipantIDs | pubmed_primary_24846672 proquest_miscellaneous_1662431220 crossref_primary_10_1109_JBHI_2014_2325017 ieee_primary_6817532 |
PublicationCentury | 2000 |
PublicationDate | 2015-March 2015-Mar 2015-3-00 20150301 |
PublicationDateYYYYMMDD | 2015-03-01 |
PublicationDate_xml | – month: 03 year: 2015 text: 2015-March |
PublicationDecade | 2010 |
PublicationPlace | United States |
PublicationPlace_xml | – name: United States |
PublicationTitle | IEEE journal of biomedical and health informatics |
PublicationTitleAbbrev | JBHI |
PublicationTitleAlternate | IEEE J Biomed Health Inform |
PublicationYear | 2015 |
Publisher | IEEE |
Publisher_xml | – name: IEEE |
References | ref35 ref13 ref12 ref15 ref31 ref30 ref33 ref11 ref32 ref10 ref2 ref1 ref16 (ref14) 0 ref19 ref18 ref24 ref23 ref26 ref25 ref20 ref22 ref21 ref28 ref27 ref29 ref8 ref7 park (ref34) 2003; 4 ref9 ref4 goldberger (ref17) 2000; 101 ref3 ref6 ref5 |
References_xml | – ident: ref20 doi: 10.1109/TIT.2007.909108 – volume: 101 start-page: 215e year: 2000 ident: ref17 article-title: Physiobank, Physiotoolkit, and Physionet: Components of a new research resource for complex physiologic signals publication-title: Circulation doi: 10.1161/01.CIR.101.23.e215 contributor: fullname: goldberger – ident: ref5 doi: 10.1109/4233.924801 – ident: ref18 doi: 10.1137/060657704 – ident: ref7 doi: 10.1109/10.846678 – ident: ref4 doi: 10.1109/MSP.2007.914731 – ident: ref15 doi: 10.1109/NEBC.2012.6207081 – ident: ref19 doi: 10.1137/S1064827596304010 – ident: ref29 doi: 10.1007/978-1-4615-3626-0 – ident: ref25 doi: 10.1023/A:1014554317692 – ident: ref21 doi: 10.1016/j.acha.2008.07.002 – ident: ref26 doi: 10.1137/090772447 – ident: ref8 doi: 10.1109/TBCAS.2012.2193668 – ident: ref16 doi: 10.1109/TIT.2010.2040894 – ident: ref30 doi: 10.1109/ICASSP.2010.5495901 – volume: 4 start-page: 36 year: 2003 ident: ref34 article-title: Time complexity analysis of SPIHT (set partitioning in hierarchy trees) image coding algorithm publication-title: J Inst Signal Process Syst contributor: fullname: park – ident: ref23 doi: 10.1016/j.acha.2009.04.002 – ident: ref13 doi: 10.1117/12.919478 – ident: ref6 doi: 10.1109/10.568915 – ident: ref33 doi: 10.1109/DSP-SPE.2013.6642561 – ident: ref22 doi: 10.1007/s10208-008-9031-3 – ident: ref31 doi: 10.1109/TITB.2005.854512 – ident: ref9 doi: 10.1109/TBME.2012.2226175 – ident: ref12 doi: 10.1109/ICASSP.2011.5946515 – ident: ref35 doi: 10.1016/j.ipl.2008.09.028 – ident: ref11 doi: 10.1109/JETCAS.2012.2220253 – ident: ref27 doi: 10.1109/TSP.2010.2051150 – ident: ref1 doi: 10.1109/MCOM.2009.5350373 – ident: ref24 doi: 10.1109/78.668544 – ident: ref10 doi: 10.1109/BioCAS.2011.6107743 – ident: ref3 doi: 10.1109/TIT.2006.871582 – ident: ref32 doi: 10.1109/TBME.2008.918465 – start-page: 83650d year: 0 ident: ref14 publication-title: Proc SPIE Defense Security and Sensing – ident: ref28 doi: 10.1109/JSSC.2011.2179451 – ident: ref2 doi: 10.1109/TBME.2011.2156795 |
SSID | ssj0000816896 |
Score | 2.4896443 |
Snippet | Recent results in telecardiology show that compressed sensing (CS) is a promising tool to lower energy consumption in wireless body area networks for... |
SourceID | proquest crossref pubmed ieee |
SourceType | Aggregation Database Index Database Publisher |
StartPage | 508 |
SubjectTerms | Algorithms Approximation algorithms Approximation methods Compressed sensing Data Compression - methods Databases, Factual Electrocardiography Electrocardiography - methods Humans Remote Sensing Technology Vectors Wavelet Analysis Wavelet transforms Wireless communication Wireless Technology |
Title | Exploiting Prior Knowledge in Compressed Sensing Wireless ECG Systems |
URI | https://ieeexplore.ieee.org/document/6817532 https://www.ncbi.nlm.nih.gov/pubmed/24846672 https://search.proquest.com/docview/1662431220 |
Volume | 19 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LS8QwEB7Ug3jx_VhfRPAkdk3S9JGjyuqqrAgqeCt5FRalK-vuxV_vJG0XFAVPTUvappmk82XmywzAMc8MRVSRRVxob61K4khKgatWmmpVIj5JjN_gPLhP-8_i9iV5mYPT2V4Y51wgn7muLwZfvh2ZqTeVnaW5jyuJP9z5nPJ6r9bMnhISSIR0XBwLEU5E0TgxGZVntxf9G8_jEl1EEAmOQh8EWKDuTTP-TSOFFCt_o82gda5WYNC2tyabvHanE901nz9COf73g1ZhuYGf5LweL2sw56p1WBw0DvYN6AVO3tBzocnDeDgak7vW6EaGFfF_jxBt3JJHz3zHWp4--4aXSO_ymjTxzzfh-ar3dNmPmkwLkYk5m0SlTLhUtHTMMmuZcVYpy7jJGTMKAWSZKauNNtSiuhdxLHPLtC1LhUfJnY23YKEaVW4HiBFOJypHvUhjQUuhpTV4lmntODMs7cBJ29vFex1QowgLESoLL6XCS6lopNSBDd9ps4pNf3XgqJVPgbPBuzhU5UbTj4KlKbaPcU47sF0LbnZzK-_d3x-6B0v46qTml-3DwmQ8dQcIOCb6MIy0L9ffznQ |
link.rule.ids | 315,786,790,802,27955,27956,55107 |
linkProvider | IEEE |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3dT9swED8hkICXMcbHAox50p6mpdiOk9SPrCoU2iKktVLfIn9FqkApKu3L_vqdnaTSpiHtKU7kRI7P9v189_MdwFeeG4qoIo-50N5alSaxlAJ3rTTTqkR8khp_wHn8kA2m4n6Wzrbg--YsjHMukM9cxxeDL98uzNqbyq6yro8riQvuDup5mtentTYWlZBCIiTk4liIcSqKxo3JqLy6_zG480wu0UEMkeI49GGABWrfLOd_6KSQZOVtvBn0zs0BjNsW13STp856pTvm11_BHP_3l97DuwaAkut6xBzClqs-wO64cbEfQT-w8uaeDU0el_PFkgxbsxuZV8SvHyHeuCU_Pfcda3kC7TM-Iv3eLWkioB_D9KY_6Q3iJtdCbBLOVnEpUy4VLR2zzFpmnFXKMm66jBmFELLMldVGG2pR4YskkV3LtC1LhVfJnU1OYLtaVO4jECOcTlUXNSNNBC2FltbgXa6148ywLIJvbW8XL3VIjSJsRagsvJQKL6WikVIER77TNhWb_orgSyufAueDd3Koyi3WrwXLMmwf45xGcFoLbvNyK--zf3_0M-wNJuNRMbp7GJ7DPjYjrdlmF7C9Wq7dJ4QfK30ZRt1v5jPRyA |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Exploiting+prior+knowledge+in+compressed+sensing+wireless+ECG+systems&rft.jtitle=IEEE+journal+of+biomedical+and+health+informatics&rft.au=Polan%C3%ADa%2C+Luisa+F&rft.au=Carrillo%2C+Rafael+E&rft.au=Blanco-Velasco%2C+Manuel&rft.au=Barner%2C+Kenneth+E&rft.date=2015-03-01&rft.eissn=2168-2208&rft.volume=19&rft.issue=2&rft.spage=508&rft.epage=519&rft_id=info:doi/10.1109%2FJBHI.2014.2325017&rft.externalDBID=NO_FULL_TEXT |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2168-2194&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2168-2194&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2168-2194&client=summon |