Cuff-Free Blood Pressure Estimation Using Pulse Transit Time and Heart Rate.
Identifieur interne : 001536 ( PubMed/Corpus ); précédent : 001535; suivant : 001537Cuff-Free Blood Pressure Estimation Using Pulse Transit Time and Heart Rate.
Auteurs : Ruiping Wang ; Wenyan Jia ; Zhi-Hong Mao ; Robert J. Sclabassi ; Mingui SunSource :
- International conference on signal processing proceedings. International Conference on Signal Processing ; 2014.
Abstract
It has been reported that the pulse transit time (PTT), the interval between the peak of the R-wave in electrocardiogram (ECG) and the fingertip photoplethysmogram (PPG), is related to arterial stiffness, and can be used to estimate the systolic blood pressure (SBP) and diastolic blood pressure (DBP). This phenomenon has been used as the basis to design portable systems for continuously cuff-less blood pressure measurement, benefiting numerous people with heart conditions. However, the PTT-based blood pressure estimation may not be sufficiently accurate because the regulation of blood pressure within the human body is a complex, multivariate physiological process. Considering the negative feedback mechanism in the blood pressure control, we introduce the heart rate (HR) and the blood pressure estimate in the previous step to obtain the current estimate. We validate this method using a clinical database. Our results show that the PTT, HR and previous estimate reduce the estimated error significantly when compared to the conventional PTT estimation approach (p<0.05).
DOI: 10.1109/ICOSP.2014.7014980
PubMed: 26213717
Links to Exploration step
pubmed:26213717Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Cuff-Free Blood Pressure Estimation Using Pulse Transit Time and Heart Rate.</title>
<author><name sortKey="Wang, Ruiping" sort="Wang, Ruiping" uniqKey="Wang R" first="Ruiping" last="Wang">Ruiping Wang</name>
<affiliation><nlm:affiliation>Department of Biomedical Engineering, Beijing Jiaotong University, Beijing, China.</nlm:affiliation>
</affiliation>
</author>
<author><name sortKey="Jia, Wenyan" sort="Jia, Wenyan" uniqKey="Jia W" first="Wenyan" last="Jia">Wenyan Jia</name>
<affiliation><nlm:affiliation>Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA.</nlm:affiliation>
</affiliation>
</author>
<author><name sortKey="Mao, Zhi Hong" sort="Mao, Zhi Hong" uniqKey="Mao Z" first="Zhi-Hong" last="Mao">Zhi-Hong Mao</name>
<affiliation><nlm:affiliation>Department of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA.</nlm:affiliation>
</affiliation>
</author>
<author><name sortKey="Sclabassi, Robert J" sort="Sclabassi, Robert J" uniqKey="Sclabassi R" first="Robert J" last="Sclabassi">Robert J. Sclabassi</name>
<affiliation><nlm:affiliation>Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.</nlm:affiliation>
</affiliation>
</author>
<author><name sortKey="Sun, Mingui" sort="Sun, Mingui" uniqKey="Sun M" first="Mingui" last="Sun">Mingui Sun</name>
<affiliation><nlm:affiliation>Computational Diagnostics, Inc., Pittsburgh, PA.</nlm:affiliation>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">PubMed</idno>
<date when="2014">2014</date>
<idno type="RBID">pubmed:26213717</idno>
<idno type="pmid">26213717</idno>
<idno type="doi">10.1109/ICOSP.2014.7014980</idno>
<idno type="wicri:Area/PubMed/Corpus">001536</idno>
<idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">001536</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en">Cuff-Free Blood Pressure Estimation Using Pulse Transit Time and Heart Rate.</title>
<author><name sortKey="Wang, Ruiping" sort="Wang, Ruiping" uniqKey="Wang R" first="Ruiping" last="Wang">Ruiping Wang</name>
<affiliation><nlm:affiliation>Department of Biomedical Engineering, Beijing Jiaotong University, Beijing, China.</nlm:affiliation>
</affiliation>
</author>
<author><name sortKey="Jia, Wenyan" sort="Jia, Wenyan" uniqKey="Jia W" first="Wenyan" last="Jia">Wenyan Jia</name>
<affiliation><nlm:affiliation>Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA.</nlm:affiliation>
</affiliation>
</author>
<author><name sortKey="Mao, Zhi Hong" sort="Mao, Zhi Hong" uniqKey="Mao Z" first="Zhi-Hong" last="Mao">Zhi-Hong Mao</name>
<affiliation><nlm:affiliation>Department of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA.</nlm:affiliation>
</affiliation>
</author>
<author><name sortKey="Sclabassi, Robert J" sort="Sclabassi, Robert J" uniqKey="Sclabassi R" first="Robert J" last="Sclabassi">Robert J. Sclabassi</name>
<affiliation><nlm:affiliation>Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.</nlm:affiliation>
</affiliation>
</author>
<author><name sortKey="Sun, Mingui" sort="Sun, Mingui" uniqKey="Sun M" first="Mingui" last="Sun">Mingui Sun</name>
<affiliation><nlm:affiliation>Computational Diagnostics, Inc., Pittsburgh, PA.</nlm:affiliation>
</affiliation>
</author>
</analytic>
<series><title level="j">International conference on signal processing proceedings. International Conference on Signal Processing</title>
<imprint><date when="2014" type="published">2014</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass></textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">It has been reported that the pulse transit time (PTT), the interval between the peak of the R-wave in electrocardiogram (ECG) and the fingertip photoplethysmogram (PPG), is related to arterial stiffness, and can be used to estimate the systolic blood pressure (SBP) and diastolic blood pressure (DBP). This phenomenon has been used as the basis to design portable systems for continuously cuff-less blood pressure measurement, benefiting numerous people with heart conditions. However, the PTT-based blood pressure estimation may not be sufficiently accurate because the regulation of blood pressure within the human body is a complex, multivariate physiological process. Considering the negative feedback mechanism in the blood pressure control, we introduce the heart rate (HR) and the blood pressure estimate in the previous step to obtain the current estimate. We validate this method using a clinical database. Our results show that the PTT, HR and previous estimate reduce the estimated error significantly when compared to the conventional PTT estimation approach (p<0.05).</div>
</front>
</TEI>
<pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">26213717</PMID>
<DateCreated><Year>2015</Year>
<Month>07</Month>
<Day>27</Day>
</DateCreated>
<DateRevised><Year>2017</Year>
<Month>02</Month>
<Day>20</Day>
</DateRevised>
<Article PubModel="Print"><Journal><JournalIssue CitedMedium="Print"><Volume>2014</Volume>
<PubDate><Year>2014</Year>
<Month>Oct</Month>
</PubDate>
</JournalIssue>
<Title>International conference on signal processing proceedings. International Conference on Signal Processing</Title>
<ISOAbbreviation>Int Conf Signal Process Proc</ISOAbbreviation>
</Journal>
<ArticleTitle>Cuff-Free Blood Pressure Estimation Using Pulse Transit Time and Heart Rate.</ArticleTitle>
<Pagination><MedlinePgn>115-118</MedlinePgn>
</Pagination>
<Abstract><AbstractText>It has been reported that the pulse transit time (PTT), the interval between the peak of the R-wave in electrocardiogram (ECG) and the fingertip photoplethysmogram (PPG), is related to arterial stiffness, and can be used to estimate the systolic blood pressure (SBP) and diastolic blood pressure (DBP). This phenomenon has been used as the basis to design portable systems for continuously cuff-less blood pressure measurement, benefiting numerous people with heart conditions. However, the PTT-based blood pressure estimation may not be sufficiently accurate because the regulation of blood pressure within the human body is a complex, multivariate physiological process. Considering the negative feedback mechanism in the blood pressure control, we introduce the heart rate (HR) and the blood pressure estimate in the previous step to obtain the current estimate. We validate this method using a clinical database. Our results show that the PTT, HR and previous estimate reduce the estimated error significantly when compared to the conventional PTT estimation approach (p<0.05).</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Wang</LastName>
<ForeName>Ruiping</ForeName>
<Initials>R</Initials>
<AffiliationInfo><Affiliation>Department of Biomedical Engineering, Beijing Jiaotong University, Beijing, China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Jia</LastName>
<ForeName>Wenyan</ForeName>
<Initials>W</Initials>
<AffiliationInfo><Affiliation>Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Mao</LastName>
<ForeName>Zhi-Hong</ForeName>
<Initials>ZH</Initials>
<AffiliationInfo><Affiliation>Department of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Sclabassi</LastName>
<ForeName>Robert J</ForeName>
<Initials>RJ</Initials>
<AffiliationInfo><Affiliation>Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Sun</LastName>
<ForeName>Mingui</ForeName>
<Initials>M</Initials>
<AffiliationInfo><Affiliation>Computational Diagnostics, Inc., Pittsburgh, PA.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<GrantList CompleteYN="Y"><Grant><GrantID>R01 CA165255</GrantID>
<Acronym>CA</Acronym>
<Agency>NCI NIH HHS</Agency>
<Country>United States</Country>
</Grant>
<Grant><GrantID>R01 EB013174</GrantID>
<Acronym>EB</Acronym>
<Agency>NIBIB NIH HHS</Agency>
<Country>United States</Country>
</Grant>
</GrantList>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
</PublicationTypeList>
</Article>
<MedlineJournalInfo><Country>United States</Country>
<MedlineTA>Int Conf Signal Process Proc</MedlineTA>
<NlmUniqueID>101616248</NlmUniqueID>
</MedlineJournalInfo>
<CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>Br J Nurs. 2012 May 24-Jun 13;21(10):621-5</RefSource>
<PMID Version="1">22875303</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>J Clin Monit Comput. 2012 Aug;26(4):267-78</RefSource>
<PMID Version="1">22695821</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Ultrason Imaging. 1979 Oct;1(4):356-67</RefSource>
<PMID Version="1">575833</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Circulation. 1981 Dec;64(6):1079-88</RefSource>
<PMID Version="1">6794930</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>IEEE Trans Biomed Eng. 2013 Apr;60(4):1080-9</RefSource>
<PMID Version="1">22868529</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Cardiovasc Eng. 2009 Mar;9(1):32-8</RefSource>
<PMID Version="1">19381806</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Heart Rhythm. 2011 Jul;8(7):1114-54</RefSource>
<PMID Version="1">21722856</PMID>
</CommentsCorrections>
</CommentsCorrectionsList>
<KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">ECG signal</Keyword>
<Keyword MajorTopicYN="N">arterial blood pressure</Keyword>
<Keyword MajorTopicYN="N">fingertip Photoplethysmogram</Keyword>
<Keyword MajorTopicYN="N">pulse transit time</Keyword>
</KeywordList>
</MedlineCitation>
<PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2015</Year>
<Month>7</Month>
<Day>28</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed"><Year>2015</Year>
<Month>7</Month>
<Day>28</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline"><Year>2015</Year>
<Month>7</Month>
<Day>28</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>ppublish</PublicationStatus>
<ArticleIdList><ArticleId IdType="pubmed">26213717</ArticleId>
<ArticleId IdType="doi">10.1109/ICOSP.2014.7014980</ArticleId>
<ArticleId IdType="pmc">PMC4512231</ArticleId>
<ArticleId IdType="mid">NIHMS706152</ArticleId>
</ArticleIdList>
<pmc-dir>nihms</pmc-dir>
</PubmedData>
</pubmed>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Amérique/explor/PittsburghV1/Data/PubMed/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 001536 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/PubMed/Corpus/biblio.hfd -nk 001536 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Wicri/Amérique |area= PittsburghV1 |flux= PubMed |étape= Corpus |type= RBID |clé= pubmed:26213717 |texte= Cuff-Free Blood Pressure Estimation Using Pulse Transit Time and Heart Rate. }}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/PubMed/Corpus/RBID.i -Sk "pubmed:26213717" \ | HfdSelect -Kh $EXPLOR_AREA/Data/PubMed/Corpus/biblio.hfd \ | NlmPubMed2Wicri -a PittsburghV1
![]() | This area was generated with Dilib version V0.6.38. | ![]() |