Cargando…

Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms on Healthy Volunteers

Physiological variation of the interval between consecutive heartbeats is known as the heart rate variability (HRV). HRV analysis is traditionally performed on electrocardiograms (ECG signals) and has become a useful tool in the diagnosis of different clinical and functional conditions. The progress...

Descripción completa

Detalles Bibliográficos
Autores principales: Sieciński, Szymon, Kostka, Paweł S., Tkacz, Ewaryst J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7472094/
https://www.ncbi.nlm.nih.gov/pubmed/32823498
http://dx.doi.org/10.3390/s20164522
_version_ 1783578910058872832
author Sieciński, Szymon
Kostka, Paweł S.
Tkacz, Ewaryst J.
author_facet Sieciński, Szymon
Kostka, Paweł S.
Tkacz, Ewaryst J.
author_sort Sieciński, Szymon
collection PubMed
description Physiological variation of the interval between consecutive heartbeats is known as the heart rate variability (HRV). HRV analysis is traditionally performed on electrocardiograms (ECG signals) and has become a useful tool in the diagnosis of different clinical and functional conditions. The progress in the sensor technique encouraged the development of alternative methods of analyzing cardiac activity: Seismocardiography and gyrocardiography. In our study we performed HRV analysis on ECG, seismocardiograms (SCG signals) and gyrocardiograms (GCG signals) using the PhysioNet Cardiovascular Toolbox. The heartbeats in ECG were detected using the Pan–Tompkins algorithm and the heartbeats in SCG and GCG signals were detected as peaks within 100 ms from the occurrence of the ECG R waves. The results of time domain, frequency domain and nonlinear HRV analysis on ECG, SCG and GCG signals are similar and this phenomenon is confirmed by very strong linear correlation of HRV indices. The differences between HRV indices obtained on ECG and SCG and on ECG and GCG were statistically insignificant and encourage using SCG or GCG for HRV estimation. Our results of HRV analysis confirm stronger correlation of HRV indices computed on ECG and GCG signals than on ECG and SCG signals because of greater tolerance to inter-subject variability and disturbances.
format Online
Article
Text
id pubmed-7472094
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-74720942020-09-04 Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms on Healthy Volunteers Sieciński, Szymon Kostka, Paweł S. Tkacz, Ewaryst J. Sensors (Basel) Article Physiological variation of the interval between consecutive heartbeats is known as the heart rate variability (HRV). HRV analysis is traditionally performed on electrocardiograms (ECG signals) and has become a useful tool in the diagnosis of different clinical and functional conditions. The progress in the sensor technique encouraged the development of alternative methods of analyzing cardiac activity: Seismocardiography and gyrocardiography. In our study we performed HRV analysis on ECG, seismocardiograms (SCG signals) and gyrocardiograms (GCG signals) using the PhysioNet Cardiovascular Toolbox. The heartbeats in ECG were detected using the Pan–Tompkins algorithm and the heartbeats in SCG and GCG signals were detected as peaks within 100 ms from the occurrence of the ECG R waves. The results of time domain, frequency domain and nonlinear HRV analysis on ECG, SCG and GCG signals are similar and this phenomenon is confirmed by very strong linear correlation of HRV indices. The differences between HRV indices obtained on ECG and SCG and on ECG and GCG were statistically insignificant and encourage using SCG or GCG for HRV estimation. Our results of HRV analysis confirm stronger correlation of HRV indices computed on ECG and GCG signals than on ECG and SCG signals because of greater tolerance to inter-subject variability and disturbances. MDPI 2020-08-13 /pmc/articles/PMC7472094/ /pubmed/32823498 http://dx.doi.org/10.3390/s20164522 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sieciński, Szymon
Kostka, Paweł S.
Tkacz, Ewaryst J.
Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms on Healthy Volunteers
title Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms on Healthy Volunteers
title_full Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms on Healthy Volunteers
title_fullStr Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms on Healthy Volunteers
title_full_unstemmed Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms on Healthy Volunteers
title_short Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms on Healthy Volunteers
title_sort heart rate variability analysis on electrocardiograms, seismocardiograms and gyrocardiograms on healthy volunteers
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7472094/
https://www.ncbi.nlm.nih.gov/pubmed/32823498
http://dx.doi.org/10.3390/s20164522
work_keys_str_mv AT siecinskiszymon heartratevariabilityanalysisonelectrocardiogramsseismocardiogramsandgyrocardiogramsonhealthyvolunteers
AT kostkapawełs heartratevariabilityanalysisonelectrocardiogramsseismocardiogramsandgyrocardiogramsonhealthyvolunteers
AT tkaczewarystj heartratevariabilityanalysisonelectrocardiogramsseismocardiogramsandgyrocardiogramsonhealthyvolunteers