Spectral Analysis of Finger Photoplethysmographic Waveform Variability in a Model of Mild to Moderate Haemorrhage
Objective Slow fluctuations in cardiovascular signals such as heart rate variability (HRV) are believed to carry important clinical information. This study investigated whether frequency spectrum analysis of the finger photoplethysmographic waveform variability (PPGV) could characterize a hypovolaem...
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creator | Middleton, Paul M. Chan, Gregory S. H. O’Lone, Emma Steel, Elizabeth Carroll, Rebecca Celler, Branko G. Lovell, Nigel H. |
description | Objective
Slow fluctuations in cardiovascular signals such as heart rate variability (HRV) are believed to carry important clinical information. This study investigated whether frequency spectrum analysis of the finger photoplethysmographic waveform variability (PPGV) could characterize a hypovolaemic response by using a blood donation as a model of controlled mild to moderate haemorrhage.
Methods
This was a prospective, observational study carried out in a convenience sample of blood donors. Spectral analysis was performed on the finger infrared photoplethysmographic waveform and on the electrocardiogram- derived R–R intervals obtained from 43 healthy volunteers during blood donation. Spectral powers were calculated from low frequency (LF), mid frequency (MF) and high frequency (HF) bands of the spectrum of HRV and the coherence-weighted cross-spectrum of PPGV. Comparison was made between the four stages of blood donation: pre-donation (PRE), first half of donation (FIRST), second half of donation (SECOND) and post-donation (POST).
Results
A significant increase in the sum of the sympathetic-related MF and respiratory HF powers of finger PPGV (in mean-scaled units) was observed in SECOND and POST (
P
< 0.01). The post-donation increase in this PPGV spectral measure occurred in 77% of the subjects, which was higher than the percentage of subjects experiencing a blood pressure drop (71% or below). Normalized LF power of HRV showed a significant rise in SECOND (
P
< 0.01) but not in POST.
Conclusions
Spectral analysis of finger PPGV may provide valuable information in addition to vital sign measurements in characterizing a hypovolaemic response. Given the limitations of the current blood loss model, further studies are required to assess the usefulness of finger PPGV for early haemorrhage detection in the clinical setting. |
doi_str_mv | 10.1007/s10877-008-9140-1 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_743471064</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>36142268</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3471-ed2432b9b828b1ded32cd6c60f0849d54a0d459e546ad26ce99bffbd7823b4933</originalsourceid><addsrcrecordid>eNqFkU1r3DAQhkVpaNK0P6CXInpoT25GH5bkYwhJU0hIoF9HIVvjXQV55Ujewv772t2FQKHtSUJ65p1hHkLeMPjIAPRZYWC0rgBM1TAJFXtGTlitRcUVk8_nuzC6YgL0MXlZygMANEawF-SYGVMDN_yEPH4ZsZuyi_R84-KuhEJTT6_CZoWZ3q_TlMaI03pXhrTKblyHjv5wP7FPeaDfXQ6uDTFMOxo21NHb5DEu9bchejql3w_ZTUivHQ4p57Vb4Sty1LtY8PXhPCXfri6_XlxXN3efPl-c31SdkJpV6LkUvG1aw03LPHrBO686BT0Y2fhaOvCybrCWynmuOmyatu9brw0XrWyEOCUf9rljTo9bLJMdQukwRrfBtC1Wy6UPKDmT7_9JqsYAMMX-C4p57ZwrM4Pv_gAf0jbPCy6WM82EUGoZkO2hLqdSMvZ2zGFweWcZ2MWv3fu1s1-7-LXLBG8Pwdt2QP9UcRA6A3wPlPlrkfjU-e-pvwAxSLAY</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>217133663</pqid></control><display><type>article</type><title>Spectral Analysis of Finger Photoplethysmographic Waveform Variability in a Model of Mild to Moderate Haemorrhage</title><source>MEDLINE</source><source>Springer Nature - Complete Springer Journals</source><creator>Middleton, Paul M. ; Chan, Gregory S. H. ; O’Lone, Emma ; Steel, Elizabeth ; Carroll, Rebecca ; Celler, Branko G. ; Lovell, Nigel H.</creator><creatorcontrib>Middleton, Paul M. ; Chan, Gregory S. H. ; O’Lone, Emma ; Steel, Elizabeth ; Carroll, Rebecca ; Celler, Branko G. ; Lovell, Nigel H.</creatorcontrib><description>Objective
Slow fluctuations in cardiovascular signals such as heart rate variability (HRV) are believed to carry important clinical information. This study investigated whether frequency spectrum analysis of the finger photoplethysmographic waveform variability (PPGV) could characterize a hypovolaemic response by using a blood donation as a model of controlled mild to moderate haemorrhage.
Methods
This was a prospective, observational study carried out in a convenience sample of blood donors. Spectral analysis was performed on the finger infrared photoplethysmographic waveform and on the electrocardiogram- derived R–R intervals obtained from 43 healthy volunteers during blood donation. Spectral powers were calculated from low frequency (LF), mid frequency (MF) and high frequency (HF) bands of the spectrum of HRV and the coherence-weighted cross-spectrum of PPGV. Comparison was made between the four stages of blood donation: pre-donation (PRE), first half of donation (FIRST), second half of donation (SECOND) and post-donation (POST).
Results
A significant increase in the sum of the sympathetic-related MF and respiratory HF powers of finger PPGV (in mean-scaled units) was observed in SECOND and POST (
P
< 0.01). The post-donation increase in this PPGV spectral measure occurred in 77% of the subjects, which was higher than the percentage of subjects experiencing a blood pressure drop (71% or below). Normalized LF power of HRV showed a significant rise in SECOND (
P
< 0.01) but not in POST.
Conclusions
Spectral analysis of finger PPGV may provide valuable information in addition to vital sign measurements in characterizing a hypovolaemic response. Given the limitations of the current blood loss model, further studies are required to assess the usefulness of finger PPGV for early haemorrhage detection in the clinical setting.</description><identifier>ISSN: 1387-1307</identifier><identifier>EISSN: 1573-2614</identifier><identifier>DOI: 10.1007/s10877-008-9140-1</identifier><identifier>PMID: 18850282</identifier><identifier>CODEN: JCMCFG</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Anesthesiology ; Artificial Intelligence ; Critical Care Medicine ; Diagnosis, Computer-Assisted - methods ; Fingers - blood supply ; Fingers - physiopathology ; Health Sciences ; Hemorrhage - diagnosis ; Hemorrhage - physiopathology ; Humans ; Intensive ; Medicine ; Medicine & Public Health ; Pattern Recognition, Automated - methods ; Photoplethysmography - methods ; Reproducibility of Results ; Sensitivity and Specificity ; Signal Processing, Computer-Assisted ; Statistics for Life Sciences</subject><ispartof>Journal of clinical monitoring and computing, 2008-10, Vol.22 (5), p.343-353</ispartof><rights>Springer Science+Business Media, LLC 2008</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3471-ed2432b9b828b1ded32cd6c60f0849d54a0d459e546ad26ce99bffbd7823b4933</citedby><cites>FETCH-LOGICAL-c3471-ed2432b9b828b1ded32cd6c60f0849d54a0d459e546ad26ce99bffbd7823b4933</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10877-008-9140-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10877-008-9140-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51298</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18850282$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Middleton, Paul M.</creatorcontrib><creatorcontrib>Chan, Gregory S. H.</creatorcontrib><creatorcontrib>O’Lone, Emma</creatorcontrib><creatorcontrib>Steel, Elizabeth</creatorcontrib><creatorcontrib>Carroll, Rebecca</creatorcontrib><creatorcontrib>Celler, Branko G.</creatorcontrib><creatorcontrib>Lovell, Nigel H.</creatorcontrib><title>Spectral Analysis of Finger Photoplethysmographic Waveform Variability in a Model of Mild to Moderate Haemorrhage</title><title>Journal of clinical monitoring and computing</title><addtitle>J Clin Monit Comput</addtitle><addtitle>J Clin Monit Comput</addtitle><description>Objective
Slow fluctuations in cardiovascular signals such as heart rate variability (HRV) are believed to carry important clinical information. This study investigated whether frequency spectrum analysis of the finger photoplethysmographic waveform variability (PPGV) could characterize a hypovolaemic response by using a blood donation as a model of controlled mild to moderate haemorrhage.
Methods
This was a prospective, observational study carried out in a convenience sample of blood donors. Spectral analysis was performed on the finger infrared photoplethysmographic waveform and on the electrocardiogram- derived R–R intervals obtained from 43 healthy volunteers during blood donation. Spectral powers were calculated from low frequency (LF), mid frequency (MF) and high frequency (HF) bands of the spectrum of HRV and the coherence-weighted cross-spectrum of PPGV. Comparison was made between the four stages of blood donation: pre-donation (PRE), first half of donation (FIRST), second half of donation (SECOND) and post-donation (POST).
Results
A significant increase in the sum of the sympathetic-related MF and respiratory HF powers of finger PPGV (in mean-scaled units) was observed in SECOND and POST (
P
< 0.01). The post-donation increase in this PPGV spectral measure occurred in 77% of the subjects, which was higher than the percentage of subjects experiencing a blood pressure drop (71% or below). Normalized LF power of HRV showed a significant rise in SECOND (
P
< 0.01) but not in POST.
Conclusions
Spectral analysis of finger PPGV may provide valuable information in addition to vital sign measurements in characterizing a hypovolaemic response. Given the limitations of the current blood loss model, further studies are required to assess the usefulness of finger PPGV for early haemorrhage detection in the clinical setting.</description><subject>Anesthesiology</subject><subject>Artificial Intelligence</subject><subject>Critical Care Medicine</subject><subject>Diagnosis, Computer-Assisted - methods</subject><subject>Fingers - blood supply</subject><subject>Fingers - physiopathology</subject><subject>Health Sciences</subject><subject>Hemorrhage - diagnosis</subject><subject>Hemorrhage - physiopathology</subject><subject>Humans</subject><subject>Intensive</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Pattern Recognition, Automated - methods</subject><subject>Photoplethysmography - methods</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><subject>Signal Processing, Computer-Assisted</subject><subject>Statistics for Life Sciences</subject><issn>1387-1307</issn><issn>1573-2614</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqFkU1r3DAQhkVpaNK0P6CXInpoT25GH5bkYwhJU0hIoF9HIVvjXQV55Ujewv772t2FQKHtSUJ65p1hHkLeMPjIAPRZYWC0rgBM1TAJFXtGTlitRcUVk8_nuzC6YgL0MXlZygMANEawF-SYGVMDN_yEPH4ZsZuyi_R84-KuhEJTT6_CZoWZ3q_TlMaI03pXhrTKblyHjv5wP7FPeaDfXQ6uDTFMOxo21NHb5DEu9bchejql3w_ZTUivHQ4p57Vb4Sty1LtY8PXhPCXfri6_XlxXN3efPl-c31SdkJpV6LkUvG1aw03LPHrBO686BT0Y2fhaOvCybrCWynmuOmyatu9brw0XrWyEOCUf9rljTo9bLJMdQukwRrfBtC1Wy6UPKDmT7_9JqsYAMMX-C4p57ZwrM4Pv_gAf0jbPCy6WM82EUGoZkO2hLqdSMvZ2zGFweWcZ2MWv3fu1s1-7-LXLBG8Pwdt2QP9UcRA6A3wPlPlrkfjU-e-pvwAxSLAY</recordid><startdate>200810</startdate><enddate>200810</enddate><creator>Middleton, Paul M.</creator><creator>Chan, Gregory S. H.</creator><creator>O’Lone, Emma</creator><creator>Steel, Elizabeth</creator><creator>Carroll, Rebecca</creator><creator>Celler, Branko G.</creator><creator>Lovell, Nigel H.</creator><general>Springer Netherlands</general><general>Springer Nature B.V</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>3V.</scope><scope>7RV</scope><scope>7SC</scope><scope>7SP</scope><scope>7U5</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>KB0</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope></search><sort><creationdate>200810</creationdate><title>Spectral Analysis of Finger Photoplethysmographic Waveform Variability in a Model of Mild to Moderate Haemorrhage</title><author>Middleton, Paul M. ; Chan, Gregory S. H. ; O’Lone, Emma ; Steel, Elizabeth ; Carroll, Rebecca ; Celler, Branko G. ; Lovell, Nigel H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3471-ed2432b9b828b1ded32cd6c60f0849d54a0d459e546ad26ce99bffbd7823b4933</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Anesthesiology</topic><topic>Artificial Intelligence</topic><topic>Critical Care Medicine</topic><topic>Diagnosis, Computer-Assisted - methods</topic><topic>Fingers - blood supply</topic><topic>Fingers - physiopathology</topic><topic>Health Sciences</topic><topic>Hemorrhage - diagnosis</topic><topic>Hemorrhage - physiopathology</topic><topic>Humans</topic><topic>Intensive</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Pattern Recognition, Automated - methods</topic><topic>Photoplethysmography - methods</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><topic>Signal Processing, Computer-Assisted</topic><topic>Statistics for Life Sciences</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Middleton, Paul M.</creatorcontrib><creatorcontrib>Chan, Gregory S. H.</creatorcontrib><creatorcontrib>O’Lone, Emma</creatorcontrib><creatorcontrib>Steel, Elizabeth</creatorcontrib><creatorcontrib>Carroll, Rebecca</creatorcontrib><creatorcontrib>Celler, Branko G.</creatorcontrib><creatorcontrib>Lovell, Nigel H.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of clinical monitoring and computing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Middleton, Paul M.</au><au>Chan, Gregory S. H.</au><au>O’Lone, Emma</au><au>Steel, Elizabeth</au><au>Carroll, Rebecca</au><au>Celler, Branko G.</au><au>Lovell, Nigel H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spectral Analysis of Finger Photoplethysmographic Waveform Variability in a Model of Mild to Moderate Haemorrhage</atitle><jtitle>Journal of clinical monitoring and computing</jtitle><stitle>J Clin Monit Comput</stitle><addtitle>J Clin Monit Comput</addtitle><date>2008-10</date><risdate>2008</risdate><volume>22</volume><issue>5</issue><spage>343</spage><epage>353</epage><pages>343-353</pages><issn>1387-1307</issn><eissn>1573-2614</eissn><coden>JCMCFG</coden><abstract>Objective
Slow fluctuations in cardiovascular signals such as heart rate variability (HRV) are believed to carry important clinical information. This study investigated whether frequency spectrum analysis of the finger photoplethysmographic waveform variability (PPGV) could characterize a hypovolaemic response by using a blood donation as a model of controlled mild to moderate haemorrhage.
Methods
This was a prospective, observational study carried out in a convenience sample of blood donors. Spectral analysis was performed on the finger infrared photoplethysmographic waveform and on the electrocardiogram- derived R–R intervals obtained from 43 healthy volunteers during blood donation. Spectral powers were calculated from low frequency (LF), mid frequency (MF) and high frequency (HF) bands of the spectrum of HRV and the coherence-weighted cross-spectrum of PPGV. Comparison was made between the four stages of blood donation: pre-donation (PRE), first half of donation (FIRST), second half of donation (SECOND) and post-donation (POST).
Results
A significant increase in the sum of the sympathetic-related MF and respiratory HF powers of finger PPGV (in mean-scaled units) was observed in SECOND and POST (
P
< 0.01). The post-donation increase in this PPGV spectral measure occurred in 77% of the subjects, which was higher than the percentage of subjects experiencing a blood pressure drop (71% or below). Normalized LF power of HRV showed a significant rise in SECOND (
P
< 0.01) but not in POST.
Conclusions
Spectral analysis of finger PPGV may provide valuable information in addition to vital sign measurements in characterizing a hypovolaemic response. Given the limitations of the current blood loss model, further studies are required to assess the usefulness of finger PPGV for early haemorrhage detection in the clinical setting.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><pmid>18850282</pmid><doi>10.1007/s10877-008-9140-1</doi><tpages>11</tpages></addata></record> |
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subjects | Anesthesiology Artificial Intelligence Critical Care Medicine Diagnosis, Computer-Assisted - methods Fingers - blood supply Fingers - physiopathology Health Sciences Hemorrhage - diagnosis Hemorrhage - physiopathology Humans Intensive Medicine Medicine & Public Health Pattern Recognition, Automated - methods Photoplethysmography - methods Reproducibility of Results Sensitivity and Specificity Signal Processing, Computer-Assisted Statistics for Life Sciences |
title | Spectral Analysis of Finger Photoplethysmographic Waveform Variability in a Model of Mild to Moderate Haemorrhage |
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