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Comparison of multiple cardiac signal acquisition technologies for heart rate variability analysis
Heart rate variability analysis is a recognized non-invasive tool that is used to assess autonomic nervous system regulation in various clinical settings and medical conditions. A wide variety of HRV analysis methods have been proposed, but they all require a certain number of cardiac beats interval...
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Published in: | Journal of clinical monitoring and computing 2020-08, Vol.34 (4), p.743-752 |
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description | Heart rate variability analysis is a recognized non-invasive tool that is used to assess autonomic nervous system regulation in various clinical settings and medical conditions. A wide variety of HRV analysis methods have been proposed, but they all require a certain number of cardiac beats intervals. There are many ways to record cardiac activity: electrocardiography, phonocardiography, plethysmocardiography, seismocardiography. However, the feasibility of performing HRV analysis with these technologies and particularly their ability to detect autonomic nervous system changes still has to be studied. In this study, we developed a technology allowing the simultaneous monitoring of electrocardiography, phonocardiography, seismocardiography, photoplethysmocardiography and piezoplethysmocardiography and investigated whether these sensors could be used for HRV analysis. We therefore tested the evolution of several HRV parameters computed from several sensors before, during and after a postural change. The main findings of our study is that even if most sensors were suitable for mean HR computation, some of them demonstrated limited agreement for several HRV analyses methods. We also demonstrated that piezoplethysmocardiography showed better agreement with ECG than other sensors for most HRV indexes. |
doi_str_mv | 10.1007/s10877-019-00382-0 |
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A wide variety of HRV analysis methods have been proposed, but they all require a certain number of cardiac beats intervals. There are many ways to record cardiac activity: electrocardiography, phonocardiography, plethysmocardiography, seismocardiography. However, the feasibility of performing HRV analysis with these technologies and particularly their ability to detect autonomic nervous system changes still has to be studied. In this study, we developed a technology allowing the simultaneous monitoring of electrocardiography, phonocardiography, seismocardiography, photoplethysmocardiography and piezoplethysmocardiography and investigated whether these sensors could be used for HRV analysis. We therefore tested the evolution of several HRV parameters computed from several sensors before, during and after a postural change. The main findings of our study is that even if most sensors were suitable for mean HR computation, some of them demonstrated limited agreement for several HRV analyses methods. We also demonstrated that piezoplethysmocardiography showed better agreement with ECG than other sensors for most HRV indexes.</description><identifier>ISSN: 1387-1307</identifier><identifier>EISSN: 1573-2614</identifier><identifier>DOI: 10.1007/s10877-019-00382-0</identifier><identifier>PMID: 31463835</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Anesthesiology ; Autonomic nervous system ; Change detection ; Critical Care Medicine ; Electrocardiography ; Feasibility studies ; Health Sciences ; Heart rate ; Intensive ; Life Sciences ; Medicine ; Medicine & Public Health ; Nervous system ; Original Research ; Phonocardiography ; Seismocardiography ; Sensors ; Statistics for Life Sciences</subject><ispartof>Journal of clinical monitoring and computing, 2020-08, Vol.34 (4), p.743-752</ispartof><rights>Springer Nature B.V. 2019</rights><rights>Springer Nature B.V. 2019.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c409t-a768674844ff0ece0a219544f8273fd5dffe4a6f3939340fb279e8b26fb96fdc3</citedby><cites>FETCH-LOGICAL-c409t-a768674844ff0ece0a219544f8273fd5dffe4a6f3939340fb279e8b26fb96fdc3</cites><orcidid>0000-0002-3727-9434</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,27903,27904</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31463835$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.univ-lille.fr/hal-04222433$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Charlier, P.</creatorcontrib><creatorcontrib>Cabon, M.</creatorcontrib><creatorcontrib>Herman, C.</creatorcontrib><creatorcontrib>Benouna, F.</creatorcontrib><creatorcontrib>Logier, R.</creatorcontrib><creatorcontrib>Houfflin-Debarge, V.</creatorcontrib><creatorcontrib>Jeanne, M.</creatorcontrib><creatorcontrib>De Jonckheere, J.</creatorcontrib><title>Comparison of multiple cardiac signal acquisition technologies for heart rate variability analysis</title><title>Journal of clinical monitoring and computing</title><addtitle>J Clin Monit Comput</addtitle><addtitle>J Clin Monit Comput</addtitle><description>Heart rate variability analysis is a recognized non-invasive tool that is used to assess autonomic nervous system regulation in various clinical settings and medical conditions. A wide variety of HRV analysis methods have been proposed, but they all require a certain number of cardiac beats intervals. There are many ways to record cardiac activity: electrocardiography, phonocardiography, plethysmocardiography, seismocardiography. However, the feasibility of performing HRV analysis with these technologies and particularly their ability to detect autonomic nervous system changes still has to be studied. In this study, we developed a technology allowing the simultaneous monitoring of electrocardiography, phonocardiography, seismocardiography, photoplethysmocardiography and piezoplethysmocardiography and investigated whether these sensors could be used for HRV analysis. We therefore tested the evolution of several HRV parameters computed from several sensors before, during and after a postural change. 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subjects | Anesthesiology Autonomic nervous system Change detection Critical Care Medicine Electrocardiography Feasibility studies Health Sciences Heart rate Intensive Life Sciences Medicine Medicine & Public Health Nervous system Original Research Phonocardiography Seismocardiography Sensors Statistics for Life Sciences |
title | Comparison of multiple cardiac signal acquisition technologies for heart rate variability analysis |
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