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The ClassA Framework: HRV Based Assessment of SNS and PNS Dynamics Without LF-HF Controversies

The powers of the low frequency (LF) and high frequency (HF) components of heart rate variability (HRV) have become the de facto standard metrics in the assessment of the stress response, and the related activities of the sympathetic nervous system (SNS) and the parasympathetic nervous system (PNS)....

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Autores principales: Adjei, Tricia, von Rosenberg, Wilhelm, Nakamura, Takashi, Chanwimalueang, Theerasak, Mandic, Danilo P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6511892/
https://www.ncbi.nlm.nih.gov/pubmed/31133868
http://dx.doi.org/10.3389/fphys.2019.00505
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author Adjei, Tricia
von Rosenberg, Wilhelm
Nakamura, Takashi
Chanwimalueang, Theerasak
Mandic, Danilo P.
author_facet Adjei, Tricia
von Rosenberg, Wilhelm
Nakamura, Takashi
Chanwimalueang, Theerasak
Mandic, Danilo P.
author_sort Adjei, Tricia
collection PubMed
description The powers of the low frequency (LF) and high frequency (HF) components of heart rate variability (HRV) have become the de facto standard metrics in the assessment of the stress response, and the related activities of the sympathetic nervous system (SNS) and the parasympathetic nervous system (PNS). However, the widely adopted physiological interpretations of the LF and HF components in SNS /PNS balance are now questioned, which puts under serious scrutiny stress assessments which employ the LF and HF components. To avoid these controversies, we here introduce the novel Classification Angle (ClassA) framework, which yields a family of metrics which quantify cardiac dynamics in three-dimensions. This is achieved using a finite-difference plot of HRV, which displays successive rates of change of HRV, and is demonstrated to provide sufficient degrees of freedom to determine cardiac deceleration and/or acceleration. The robustness and accuracy of the novel ClassA framework is verified using HRV signals from ten males, recorded during standardized stress tests, consisting of rest, mental arithmetic, meditation, exercise and further meditation. Comparative statistical testing demonstrates that unlike the existing LF-HF metrics, the ClassA metrics are capable of distinguishing both the physical and mental stress epochs from the epochs of no stress, with statistical significance (Bonferroni corrected p-value ≤ 0.025); HF was able to distinguish physical stress from no stress, but was not able to identify mental stress. The ClassA results also indicated that at moderate levels of stress, the extent of parasympathetic withdrawal was greater than the extent of sympathetic activation. Finally, the analyses and the experimental results provide conclusive evidence that the proposed nonlinear approach to quantify cardiac activity from HRV resolves three critical obstacles to current HRV stress assessments: (i) it is not based on controversial assumptions of balance between the LF and HF powers; (ii) its temporal resolution when estimating parasympathetic dominance is as little as 10 s of HRV data, while only 60 s to estimate sympathetic dominance; (iii) unlike LF and HF analyses, the ClassA framework does not require the prohibitive assumption of signal stationarity. The ClassA framework is unique in offering HRV based stress analysis in three-dimensions.
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spelling pubmed-65118922019-05-27 The ClassA Framework: HRV Based Assessment of SNS and PNS Dynamics Without LF-HF Controversies Adjei, Tricia von Rosenberg, Wilhelm Nakamura, Takashi Chanwimalueang, Theerasak Mandic, Danilo P. Front Physiol Physiology The powers of the low frequency (LF) and high frequency (HF) components of heart rate variability (HRV) have become the de facto standard metrics in the assessment of the stress response, and the related activities of the sympathetic nervous system (SNS) and the parasympathetic nervous system (PNS). However, the widely adopted physiological interpretations of the LF and HF components in SNS /PNS balance are now questioned, which puts under serious scrutiny stress assessments which employ the LF and HF components. To avoid these controversies, we here introduce the novel Classification Angle (ClassA) framework, which yields a family of metrics which quantify cardiac dynamics in three-dimensions. This is achieved using a finite-difference plot of HRV, which displays successive rates of change of HRV, and is demonstrated to provide sufficient degrees of freedom to determine cardiac deceleration and/or acceleration. The robustness and accuracy of the novel ClassA framework is verified using HRV signals from ten males, recorded during standardized stress tests, consisting of rest, mental arithmetic, meditation, exercise and further meditation. Comparative statistical testing demonstrates that unlike the existing LF-HF metrics, the ClassA metrics are capable of distinguishing both the physical and mental stress epochs from the epochs of no stress, with statistical significance (Bonferroni corrected p-value ≤ 0.025); HF was able to distinguish physical stress from no stress, but was not able to identify mental stress. The ClassA results also indicated that at moderate levels of stress, the extent of parasympathetic withdrawal was greater than the extent of sympathetic activation. Finally, the analyses and the experimental results provide conclusive evidence that the proposed nonlinear approach to quantify cardiac activity from HRV resolves three critical obstacles to current HRV stress assessments: (i) it is not based on controversial assumptions of balance between the LF and HF powers; (ii) its temporal resolution when estimating parasympathetic dominance is as little as 10 s of HRV data, while only 60 s to estimate sympathetic dominance; (iii) unlike LF and HF analyses, the ClassA framework does not require the prohibitive assumption of signal stationarity. The ClassA framework is unique in offering HRV based stress analysis in three-dimensions. Frontiers Media S.A. 2019-04-30 /pmc/articles/PMC6511892/ /pubmed/31133868 http://dx.doi.org/10.3389/fphys.2019.00505 Text en Copyright © 2019 Adjei, von Rosenberg, Nakamura, Chanwimalueang and Mandic. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Adjei, Tricia
von Rosenberg, Wilhelm
Nakamura, Takashi
Chanwimalueang, Theerasak
Mandic, Danilo P.
The ClassA Framework: HRV Based Assessment of SNS and PNS Dynamics Without LF-HF Controversies
title The ClassA Framework: HRV Based Assessment of SNS and PNS Dynamics Without LF-HF Controversies
title_full The ClassA Framework: HRV Based Assessment of SNS and PNS Dynamics Without LF-HF Controversies
title_fullStr The ClassA Framework: HRV Based Assessment of SNS and PNS Dynamics Without LF-HF Controversies
title_full_unstemmed The ClassA Framework: HRV Based Assessment of SNS and PNS Dynamics Without LF-HF Controversies
title_short The ClassA Framework: HRV Based Assessment of SNS and PNS Dynamics Without LF-HF Controversies
title_sort classa framework: hrv based assessment of sns and pns dynamics without lf-hf controversies
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6511892/
https://www.ncbi.nlm.nih.gov/pubmed/31133868
http://dx.doi.org/10.3389/fphys.2019.00505
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