Cardiac and Autonomic Dysfunctions Assessed Through Recurrence Quantitative Analysis of Electrocardiogram Signals and an Application to the 6-Hydroxydopamine Parkinson’s Disease Animal Model

A classic method to evaluate autonomic dysfunction is through the evaluation of heart rate variability (HRV). HRV provides a series of coefficients, such as Standard Deviation of n-n intervals (SDNN) and Root Mean Square of Successive Differences (RMSSD), which have well-established physiological as...

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Autores principales:	Lucas Shinoda, Laís Damasceno, Leandro Freitas, Ruy Campos, Sergio Cravo, Carla A. Scorza, Fúlvio A. Scorza, Jean Faber
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	recurrence quantitative analysis Poincaré map Parkinson’s disease computational ECG model 6-OHDA animal model HRV (heart rate variability) and ECG-complexes Physiology QP1-981
Acceso en línea:	https://doaj.org/article/57a7f3e2bc024dfc93b82d9d5f1f65c3
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spelling	oai:doaj.org-article:57a7f3e2bc024dfc93b82d9d5f1f65c32021-11-30T19:42:32ZCardiac and Autonomic Dysfunctions Assessed Through Recurrence Quantitative Analysis of Electrocardiogram Signals and an Application to the 6-Hydroxydopamine Parkinson’s Disease Animal Model1664-042X10.3389/fphys.2021.725218https://doaj.org/article/57a7f3e2bc024dfc93b82d9d5f1f65c32021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fphys.2021.725218/fullhttps://doaj.org/toc/1664-042XA classic method to evaluate autonomic dysfunction is through the evaluation of heart rate variability (HRV). HRV provides a series of coefficients, such as Standard Deviation of n-n intervals (SDNN) and Root Mean Square of Successive Differences (RMSSD), which have well-established physiological associations. However, using only electrocardiogram (ECG) signals, it is difficult to identify proper autonomic activity, and the standard techniques are not sensitive and robust enough to distinguish pure autonomic modulation in heart dynamics from cardiac dysfunctions. In this proof-of-concept study we propose the use of Poincaré mapping and Recurrence Quantification Analysis (RQA) to identify and characterize stochasticity and chaoticity dynamics in ECG recordings. By applying these non-linear techniques in the ECG signals recorded from a set of Parkinson’s disease (PD) animal model 6-hydroxydopamine (6-OHDA), we showed that they present less variability in long time epochs and more stochasticity in short-time epochs, in their autonomic dynamics, when compared with those of the sham group. These results suggest that PD animal models present more “rigid heart rate” associated with “trembling ECG” and bradycardia, which are direct expressions of Parkinsonian symptoms. We also compared the RQA factors calculated from the ECG of animal models using four computational ECG signals under different noise and autonomic modulatory conditions, emulating the main ECG features of atrial fibrillation and QT-long syndrome.Lucas ShinodaLaís DamascenoLeandro FreitasRuy CamposSergio CravoCarla A. ScorzaFúlvio A. ScorzaJean FaberJean FaberFrontiers Media S.A.articlerecurrence quantitative analysisPoincaré mapParkinson’s diseasecomputational ECG model6-OHDA animal modelHRV (heart rate variability) and ECG-complexesPhysiologyQP1-981ENFrontiers in Physiology, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	recurrence quantitative analysis Poincaré map Parkinson’s disease computational ECG model 6-OHDA animal model HRV (heart rate variability) and ECG-complexes Physiology QP1-981
spellingShingle	recurrence quantitative analysis Poincaré map Parkinson’s disease computational ECG model 6-OHDA animal model HRV (heart rate variability) and ECG-complexes Physiology QP1-981 Lucas Shinoda Laís Damasceno Leandro Freitas Ruy Campos Sergio Cravo Carla A. Scorza Fúlvio A. Scorza Jean Faber Jean Faber Cardiac and Autonomic Dysfunctions Assessed Through Recurrence Quantitative Analysis of Electrocardiogram Signals and an Application to the 6-Hydroxydopamine Parkinson’s Disease Animal Model
description	A classic method to evaluate autonomic dysfunction is through the evaluation of heart rate variability (HRV). HRV provides a series of coefficients, such as Standard Deviation of n-n intervals (SDNN) and Root Mean Square of Successive Differences (RMSSD), which have well-established physiological associations. However, using only electrocardiogram (ECG) signals, it is difficult to identify proper autonomic activity, and the standard techniques are not sensitive and robust enough to distinguish pure autonomic modulation in heart dynamics from cardiac dysfunctions. In this proof-of-concept study we propose the use of Poincaré mapping and Recurrence Quantification Analysis (RQA) to identify and characterize stochasticity and chaoticity dynamics in ECG recordings. By applying these non-linear techniques in the ECG signals recorded from a set of Parkinson’s disease (PD) animal model 6-hydroxydopamine (6-OHDA), we showed that they present less variability in long time epochs and more stochasticity in short-time epochs, in their autonomic dynamics, when compared with those of the sham group. These results suggest that PD animal models present more “rigid heart rate” associated with “trembling ECG” and bradycardia, which are direct expressions of Parkinsonian symptoms. We also compared the RQA factors calculated from the ECG of animal models using four computational ECG signals under different noise and autonomic modulatory conditions, emulating the main ECG features of atrial fibrillation and QT-long syndrome.
format	article
author	Lucas Shinoda Laís Damasceno Leandro Freitas Ruy Campos Sergio Cravo Carla A. Scorza Fúlvio A. Scorza Jean Faber Jean Faber
author_facet	Lucas Shinoda Laís Damasceno Leandro Freitas Ruy Campos Sergio Cravo Carla A. Scorza Fúlvio A. Scorza Jean Faber Jean Faber
author_sort	Lucas Shinoda
title	Cardiac and Autonomic Dysfunctions Assessed Through Recurrence Quantitative Analysis of Electrocardiogram Signals and an Application to the 6-Hydroxydopamine Parkinson’s Disease Animal Model
title_short	Cardiac and Autonomic Dysfunctions Assessed Through Recurrence Quantitative Analysis of Electrocardiogram Signals and an Application to the 6-Hydroxydopamine Parkinson’s Disease Animal Model
title_full	Cardiac and Autonomic Dysfunctions Assessed Through Recurrence Quantitative Analysis of Electrocardiogram Signals and an Application to the 6-Hydroxydopamine Parkinson’s Disease Animal Model
title_fullStr	Cardiac and Autonomic Dysfunctions Assessed Through Recurrence Quantitative Analysis of Electrocardiogram Signals and an Application to the 6-Hydroxydopamine Parkinson’s Disease Animal Model
title_full_unstemmed	Cardiac and Autonomic Dysfunctions Assessed Through Recurrence Quantitative Analysis of Electrocardiogram Signals and an Application to the 6-Hydroxydopamine Parkinson’s Disease Animal Model
title_sort	cardiac and autonomic dysfunctions assessed through recurrence quantitative analysis of electrocardiogram signals and an application to the 6-hydroxydopamine parkinson’s disease animal model
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/57a7f3e2bc024dfc93b82d9d5f1f65c3
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Cardiac and Autonomic Dysfunctions Assessed Through Recurrence Quantitative Analysis of Electrocardiogram Signals and an Application to the 6-Hydroxydopamine Parkinson’s Disease Animal Model

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