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Detection of Aortic Valve Opening and Estimation of Pre-Ejection Period in Forcecardiography Recordings
Forcecardiography (FCG) is a novel technique that measures the local forces induced on the chest wall by the mechanical activity of the heart. Specific piezoresistive or piezoelectric force sensors are placed on subjects’ thorax to measure these very small forces. The FCG signal can be divided into...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8945374/ https://www.ncbi.nlm.nih.gov/pubmed/35324778 http://dx.doi.org/10.3390/bioengineering9030089 |
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author | Centracchio, Jessica Andreozzi, Emilio Esposito, Daniele Gargiulo, Gaetano Dario Bifulco, Paolo |
author_facet | Centracchio, Jessica Andreozzi, Emilio Esposito, Daniele Gargiulo, Gaetano Dario Bifulco, Paolo |
author_sort | Centracchio, Jessica |
collection | PubMed |
description | Forcecardiography (FCG) is a novel technique that measures the local forces induced on the chest wall by the mechanical activity of the heart. Specific piezoresistive or piezoelectric force sensors are placed on subjects’ thorax to measure these very small forces. The FCG signal can be divided into three components: low-frequency FCG, high-frequency FCG (HF-FCG) and heart sound FCG. HF-FCG has been shown to share a high similarity with the Seismocardiogram (SCG), which is commonly acquired via small accelerometers and is mainly used to locate specific fiducial markers corresponding to essential events of the cardiac cycle (e.g., heart valves opening and closure, peaks of blood flow). However, HF-FCG has not yet been demonstrated to provide the timings of these markers with reasonable accuracy. This study addresses the detection of the aortic valve opening (AO) marker in FCG signals. To this aim, simultaneous recordings from FCG and SCG sensors were acquired, together with Electrocardiogram (ECG) recordings, from a few healthy subjects at rest, both during quiet breathing and apnea. The AO markers were located in both SCG and FCG signals to obtain pre-ejection periods (PEP) estimates, which were compared via statistical analyses. The PEPs estimated from FCG and SCG showed a strong linear relationship (r > 0.95) with a practically unit slope, and 95% of their differences were found to be distributed within ± 4.6 ms around small biases of approximately 1 ms, corresponding to percentage differences lower than 5% of the mean measured PEP. These preliminary results suggest that FCG can provide accurate AO timings and PEP estimates. |
format | Online Article Text |
id | pubmed-8945374 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-89453742022-03-25 Detection of Aortic Valve Opening and Estimation of Pre-Ejection Period in Forcecardiography Recordings Centracchio, Jessica Andreozzi, Emilio Esposito, Daniele Gargiulo, Gaetano Dario Bifulco, Paolo Bioengineering (Basel) Article Forcecardiography (FCG) is a novel technique that measures the local forces induced on the chest wall by the mechanical activity of the heart. Specific piezoresistive or piezoelectric force sensors are placed on subjects’ thorax to measure these very small forces. The FCG signal can be divided into three components: low-frequency FCG, high-frequency FCG (HF-FCG) and heart sound FCG. HF-FCG has been shown to share a high similarity with the Seismocardiogram (SCG), which is commonly acquired via small accelerometers and is mainly used to locate specific fiducial markers corresponding to essential events of the cardiac cycle (e.g., heart valves opening and closure, peaks of blood flow). However, HF-FCG has not yet been demonstrated to provide the timings of these markers with reasonable accuracy. This study addresses the detection of the aortic valve opening (AO) marker in FCG signals. To this aim, simultaneous recordings from FCG and SCG sensors were acquired, together with Electrocardiogram (ECG) recordings, from a few healthy subjects at rest, both during quiet breathing and apnea. The AO markers were located in both SCG and FCG signals to obtain pre-ejection periods (PEP) estimates, which were compared via statistical analyses. The PEPs estimated from FCG and SCG showed a strong linear relationship (r > 0.95) with a practically unit slope, and 95% of their differences were found to be distributed within ± 4.6 ms around small biases of approximately 1 ms, corresponding to percentage differences lower than 5% of the mean measured PEP. These preliminary results suggest that FCG can provide accurate AO timings and PEP estimates. MDPI 2022-02-22 /pmc/articles/PMC8945374/ /pubmed/35324778 http://dx.doi.org/10.3390/bioengineering9030089 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Centracchio, Jessica Andreozzi, Emilio Esposito, Daniele Gargiulo, Gaetano Dario Bifulco, Paolo Detection of Aortic Valve Opening and Estimation of Pre-Ejection Period in Forcecardiography Recordings |
title | Detection of Aortic Valve Opening and Estimation of Pre-Ejection Period in Forcecardiography Recordings |
title_full | Detection of Aortic Valve Opening and Estimation of Pre-Ejection Period in Forcecardiography Recordings |
title_fullStr | Detection of Aortic Valve Opening and Estimation of Pre-Ejection Period in Forcecardiography Recordings |
title_full_unstemmed | Detection of Aortic Valve Opening and Estimation of Pre-Ejection Period in Forcecardiography Recordings |
title_short | Detection of Aortic Valve Opening and Estimation of Pre-Ejection Period in Forcecardiography Recordings |
title_sort | detection of aortic valve opening and estimation of pre-ejection period in forcecardiography recordings |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8945374/ https://www.ncbi.nlm.nih.gov/pubmed/35324778 http://dx.doi.org/10.3390/bioengineering9030089 |
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