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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Bibliographic Details
Published in:Journal of clinical monitoring and computing 2020-08, Vol.34 (4), p.743-752
Main Authors: Charlier, P., Cabon, M., Herman, C., Benouna, F., Logier, R., Houfflin-Debarge, V., Jeanne, M., De Jonckheere, J.
Format: Article
Language:English
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
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Summary: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.
ISSN:1387-1307
1573-2614
DOI:10.1007/s10877-019-00382-0