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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Physiol. | doi: 10.3389/fphys.2019.00505

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

  • 1Faculty of Engineering, Imperial College London, United Kingdom

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 finitedifference
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 standardised 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 seconds of HRV data, while only 60 seconds 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.

Keywords: Autonomic Nervous System, Heart rate variability, LF, hf, Second-Order-Difference-Plot

Received: 11 Jan 2019; Accepted: 09 Apr 2019.

Edited by:

Zbigniew R. Struzik, The University of Tokyo, Japan

Reviewed by:

Junichiro Hayano, Graduate School of Medical Sciences, Nagoya City University, Japan
Alberto Porta, University of Milan, Italy  

Copyright: © 2019 Adjei, von Rosenberg and Mandic. 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.

* Correspondence:
Ms. Tricia Adjei, Faculty of Engineering, Imperial College London, London, United Kingdom, t.adjei15@imperial.ac.uk
Dr. Wilhelm von Rosenberg, Faculty of Engineering, Imperial College London, London, United Kingdom, wilhelm.von-rosenberg12@imperial.ac.uk