Arterial pressure pulse wave separation analysis using a multi-Gaussian decomposition model
Methods for separating the forward-backward components from blood pulse waves rely on simultaneously measured pressure and flow velocity from a target artery site. Modelling approaches for flow velocity simplify the wave separation analysis (WSA), providing a methodological and instrumentational adv...
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| Veröffentlicht in: | Physiological measurement 2022-05, Vol.43 (5), p.55005 |
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| creator | Manoj, Rahul Raj, Kiran V Nabeel, P M Sivaprakasam, Mohanasankar Joseph, Jayaraj |
| description | Methods for separating the forward-backward components from blood pulse waves rely on simultaneously measured pressure and flow velocity from a target artery site. Modelling approaches for flow velocity simplify the wave separation analysis (WSA), providing a methodological and instrumentational advantage over the former; however, current methods are limited to the aortic site. In this work, a multi-Gaussian decomposition (MGD) modelled WSA (MGD
) is developed for a non-aortic site such as the carotid artery. While the model is an adaptation of the existing wave separation theory, it does not rely on the information of measured or modelled flow velocity.
The proposed model decomposes the arterial pressure waveform using weighted and shifted multi-Gaussians, which are then uniquely combined to yield the forward (
(
)) and backward (
(
)) pressure wave. A study using the database of healthy (virtual) subjects was used to evaluate the performance of MGD
at the carotid artery and was compared against reference flow-based WSA methods.
The MGD modelled pressure waveform yielded a root-mean-square error (RMSE) |
| doi_str_mv | 10.1088/1361-6579/ac6e56 |
| format | Article |
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) is developed for a non-aortic site such as the carotid artery. While the model is an adaptation of the existing wave separation theory, it does not rely on the information of measured or modelled flow velocity.
The proposed model decomposes the arterial pressure waveform using weighted and shifted multi-Gaussians, which are then uniquely combined to yield the forward (
(
)) and backward (
(
)) pressure wave. A study using the database of healthy (virtual) subjects was used to evaluate the performance of MGD
at the carotid artery and was compared against reference flow-based WSA methods.
The MGD modelled pressure waveform yielded a root-mean-square error (RMSE) < 0.35 mmHg. Reliable forward-backward components with a group average RMSE <2.5 mmHg for
(
) and
(
) were obtained. When compared with the reference counterparts, the pulse pressures (Δ
and Δ
), as well as reflection quantification indices, showed a statistically significant strong correlation (
> 0.96,
< 0.0001) and (
> 0.83,
< 0.0001) respectively, with an insignificant (
> 0.05) bias.
This study reports WSA for carotid pressure waveforms without assumptions on flow conditions. The proposed method has the potential to adapt and widen the vascular health assessment techniques incorporating pulse wave dynamics.</description><identifier>ISSN: 0967-3334</identifier><identifier>EISSN: 1361-6579</identifier><identifier>DOI: 10.1088/1361-6579/ac6e56</identifier><identifier>PMID: 35537402</identifier><identifier>CODEN: PMEAE3</identifier><language>eng</language><publisher>England: IOP Publishing</publisher><subject>Aorta ; Arterial Pressure ; Blood Pressure ; Carotid Arteries ; Humans ; modelling of pulse wave ; multi-Gaussian ; Pulse Wave Analysis - methods ; pulse wave reflection ; reflection index ; reflection magnitude ; wave intensity analysis ; wave separation analysis</subject><ispartof>Physiological measurement, 2022-05, Vol.43 (5), p.55005</ispartof><rights>2022 Institute of Physics and Engineering in Medicine</rights><rights>2022 Institute of Physics and Engineering in Medicine.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c284t-5a0f639a62289f3b696854e0f8bc267d403e4ea9ef5082699c5368dbc7dd4ea43</citedby><cites>FETCH-LOGICAL-c284t-5a0f639a62289f3b696854e0f8bc267d403e4ea9ef5082699c5368dbc7dd4ea43</cites><orcidid>0000-0002-7279-9099 ; 0000-0001-7280-0048 ; 0000-0003-4078-6856 ; 0000-0001-5017-5018</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.1088/1361-6579/ac6e56/pdf$$EPDF$$P50$$Giop$$H</linktopdf><link.rule.ids>314,776,780,27901,27902,53821,53868</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35537402$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Manoj, Rahul</creatorcontrib><creatorcontrib>Raj, Kiran V</creatorcontrib><creatorcontrib>Nabeel, P M</creatorcontrib><creatorcontrib>Sivaprakasam, Mohanasankar</creatorcontrib><creatorcontrib>Joseph, Jayaraj</creatorcontrib><title>Arterial pressure pulse wave separation analysis using a multi-Gaussian decomposition model</title><title>Physiological measurement</title><addtitle>PMEA</addtitle><addtitle>Physiol. Meas</addtitle><description>Methods for separating the forward-backward components from blood pulse waves rely on simultaneously measured pressure and flow velocity from a target artery site. Modelling approaches for flow velocity simplify the wave separation analysis (WSA), providing a methodological and instrumentational advantage over the former; however, current methods are limited to the aortic site. In this work, a multi-Gaussian decomposition (MGD) modelled WSA (MGD
) is developed for a non-aortic site such as the carotid artery. While the model is an adaptation of the existing wave separation theory, it does not rely on the information of measured or modelled flow velocity.
The proposed model decomposes the arterial pressure waveform using weighted and shifted multi-Gaussians, which are then uniquely combined to yield the forward (
(
)) and backward (
(
)) pressure wave. A study using the database of healthy (virtual) subjects was used to evaluate the performance of MGD
at the carotid artery and was compared against reference flow-based WSA methods.
The MGD modelled pressure waveform yielded a root-mean-square error (RMSE) < 0.35 mmHg. Reliable forward-backward components with a group average RMSE <2.5 mmHg for
(
) and
(
) were obtained. When compared with the reference counterparts, the pulse pressures (Δ
and Δ
), as well as reflection quantification indices, showed a statistically significant strong correlation (
> 0.96,
< 0.0001) and (
> 0.83,
< 0.0001) respectively, with an insignificant (
> 0.05) bias.
This study reports WSA for carotid pressure waveforms without assumptions on flow conditions. The proposed method has the potential to adapt and widen the vascular health assessment techniques incorporating pulse wave dynamics.</description><subject>Aorta</subject><subject>Arterial Pressure</subject><subject>Blood Pressure</subject><subject>Carotid Arteries</subject><subject>Humans</subject><subject>modelling of pulse wave</subject><subject>multi-Gaussian</subject><subject>Pulse Wave Analysis - methods</subject><subject>pulse wave reflection</subject><subject>reflection index</subject><subject>reflection magnitude</subject><subject>wave intensity analysis</subject><subject>wave separation analysis</subject><issn>0967-3334</issn><issn>1361-6579</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kL9P3TAUha2qqLwCO1PlsUMDjn_FGRFqaSUkFpgYrPuSG2SUxK5v3Ir_nrw-SpcyXenoO-dKH2OntTirhXPntbJ1ZU3TnkNn0dh3bPMavWcb0dqmUkrpQ_aR6FGIunbSfGCHyhjVaCE37P4iL5gDjDxlJCoZeSojIf8Nv5ATJsiwhDhzmGF8okC8UJgfOPCpjEuorqAQBZh5j12cUqTwh55ij-MxOxhg3Tp5uUfs7tvX28vv1fXN1Y_Li-uqk04vlQExWNWCldK1g9ra1jqjUQxu20nb9Foo1AgtDkY4adu2M8q6fts1fb_mWh2xz_vdlOPPgrT4KVCH4wgzxkJeWiuNttqJFRV7tMuRKOPgUw4T5CdfC79T6nf-_M6f3ytdK59e1st2wv618Nfhv_chJv8YS15NkU8TgtfKGy-MEcL41A8r-uU_6JuvnwFkfI6w</recordid><startdate>20220531</startdate><enddate>20220531</enddate><creator>Manoj, Rahul</creator><creator>Raj, Kiran V</creator><creator>Nabeel, P M</creator><creator>Sivaprakasam, Mohanasankar</creator><creator>Joseph, Jayaraj</creator><general>IOP Publishing</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-7279-9099</orcidid><orcidid>https://orcid.org/0000-0001-7280-0048</orcidid><orcidid>https://orcid.org/0000-0003-4078-6856</orcidid><orcidid>https://orcid.org/0000-0001-5017-5018</orcidid></search><sort><creationdate>20220531</creationdate><title>Arterial pressure pulse wave separation analysis using a multi-Gaussian decomposition model</title><author>Manoj, Rahul ; Raj, Kiran V ; Nabeel, P M ; Sivaprakasam, Mohanasankar ; Joseph, Jayaraj</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c284t-5a0f639a62289f3b696854e0f8bc267d403e4ea9ef5082699c5368dbc7dd4ea43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Aorta</topic><topic>Arterial Pressure</topic><topic>Blood Pressure</topic><topic>Carotid Arteries</topic><topic>Humans</topic><topic>modelling of pulse wave</topic><topic>multi-Gaussian</topic><topic>Pulse Wave Analysis - methods</topic><topic>pulse wave reflection</topic><topic>reflection index</topic><topic>reflection magnitude</topic><topic>wave intensity analysis</topic><topic>wave separation analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Manoj, Rahul</creatorcontrib><creatorcontrib>Raj, Kiran V</creatorcontrib><creatorcontrib>Nabeel, P M</creatorcontrib><creatorcontrib>Sivaprakasam, Mohanasankar</creatorcontrib><creatorcontrib>Joseph, Jayaraj</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Physiological measurement</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Manoj, Rahul</au><au>Raj, Kiran V</au><au>Nabeel, P M</au><au>Sivaprakasam, Mohanasankar</au><au>Joseph, Jayaraj</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Arterial pressure pulse wave separation analysis using a multi-Gaussian decomposition model</atitle><jtitle>Physiological measurement</jtitle><stitle>PMEA</stitle><addtitle>Physiol. Meas</addtitle><date>2022-05-31</date><risdate>2022</risdate><volume>43</volume><issue>5</issue><spage>55005</spage><pages>55005-</pages><issn>0967-3334</issn><eissn>1361-6579</eissn><coden>PMEAE3</coden><abstract>Methods for separating the forward-backward components from blood pulse waves rely on simultaneously measured pressure and flow velocity from a target artery site. Modelling approaches for flow velocity simplify the wave separation analysis (WSA), providing a methodological and instrumentational advantage over the former; however, current methods are limited to the aortic site. In this work, a multi-Gaussian decomposition (MGD) modelled WSA (MGD
) is developed for a non-aortic site such as the carotid artery. While the model is an adaptation of the existing wave separation theory, it does not rely on the information of measured or modelled flow velocity.
The proposed model decomposes the arterial pressure waveform using weighted and shifted multi-Gaussians, which are then uniquely combined to yield the forward (
(
)) and backward (
(
)) pressure wave. A study using the database of healthy (virtual) subjects was used to evaluate the performance of MGD
at the carotid artery and was compared against reference flow-based WSA methods.
The MGD modelled pressure waveform yielded a root-mean-square error (RMSE) < 0.35 mmHg. Reliable forward-backward components with a group average RMSE <2.5 mmHg for
(
) and
(
) were obtained. When compared with the reference counterparts, the pulse pressures (Δ
and Δ
), as well as reflection quantification indices, showed a statistically significant strong correlation (
> 0.96,
< 0.0001) and (
> 0.83,
< 0.0001) respectively, with an insignificant (
> 0.05) bias.
This study reports WSA for carotid pressure waveforms without assumptions on flow conditions. The proposed method has the potential to adapt and widen the vascular health assessment techniques incorporating pulse wave dynamics.</abstract><cop>England</cop><pub>IOP Publishing</pub><pmid>35537402</pmid><doi>10.1088/1361-6579/ac6e56</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-7279-9099</orcidid><orcidid>https://orcid.org/0000-0001-7280-0048</orcidid><orcidid>https://orcid.org/0000-0003-4078-6856</orcidid><orcidid>https://orcid.org/0000-0001-5017-5018</orcidid></addata></record> |
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| subjects | Aorta Arterial Pressure Blood Pressure Carotid Arteries Humans modelling of pulse wave multi-Gaussian Pulse Wave Analysis - methods pulse wave reflection reflection index reflection magnitude wave intensity analysis wave separation analysis |
| title | Arterial pressure pulse wave separation analysis using a multi-Gaussian decomposition model |
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