Imperial College London
Portrait Picture

ProfessorDaniloMandic

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor of Machine Intelligence
 
 
 
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Contact

 

+44 (0)20 7594 6271d.mandic Website

 
 
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Assistant

 

Miss Vanessa Rodriguez-Gonzalez +44 (0)20 7594 6267

 
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Location

 

813Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Adjei:2019:10.3389/fphys.2019.00505,
author = {Adjei, T and von, Rosenberg W and Nakamura, T and Chanwimalueang, T and Mandic, D},
doi = {10.3389/fphys.2019.00505},
journal = {Frontiers in Physiology},
title = {The ClassA framework: HRV based assessment of SNS and PNS dynamics without LF-HF controversies},
url = {http://dx.doi.org/10.3389/fphys.2019.00505},
volume = {10},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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
AU  - Adjei,T
AU  - von,Rosenberg W
AU  - Nakamura,T
AU  - Chanwimalueang,T
AU  - Mandic,D
DO  - 10.3389/fphys.2019.00505
PY  - 2019///
SN  - 1664-042X
TI  - The ClassA framework: HRV based assessment of SNS and PNS dynamics without LF-HF controversies
T2  - Frontiers in Physiology
UR  - http://dx.doi.org/10.3389/fphys.2019.00505
UR  - http://hdl.handle.net/10044/1/70184
VL  - 10
ER  -
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