Comments of the MRIS about the scientific report in Nature «Single-lead ECG based autonomic nervous system assessment for meditation monitoring» – PETER GAMMA (Director & Physiologist), MEDITATION RESEARCH INSTITUTE SWITZERLAND (MRIS)

Last Updated on January 27, 2024 by pg@petergamma.org

https://www.nature.com/articles/s41598-022-27121-x

If we look at the

Abstract

«We propose a single-lead ECG-based heart rate variability (HRV) analysis algorithm to quantify autonomic nervous system activity during meditation. Respiratory sinus arrhythmia (RSA) induced by breathing is a dominant component of HRV, but its frequency depends on an individual’s breathing speed. To address this RSA issue, we designed a novel HRV tachogram decomposition algorithm and new HRV indices. The proposed method was validated by using a simulation, and applied to our experimental (mindfulness meditation) data and the WESAD open-source data. During meditation, our proposed HRV indices related to vagal and sympathetic tones were significantly increased (p < 0.000005) and decreased (p < 0.000005), respectively. These results were consistent with self-reports and experimental protocols, and identified parasympathetic activation and sympathetic inhibition during meditation. In conclusion, the proposed method successfully assessed autonomic nervous system activity during meditation when respiration influences disrupted classical HRV. The proposed method can be considered a reliable approach to quantify autonomic nervous system activity.»

And the

Conclusions

«To precisely assess autonomic nervous system activity, we proposed a novel tachogram decomposition algorithm (ZLE) and new HRV indices (IDXPNA and IDXSNA). ZLE clearly decomposed xRAW into RSA and R-f, and IDXPNA and IDXSNA identified parasympathetic activation and sympathetic inhibition during meditation, respectively. This study may be the first report on the identification of cardiac sympathetic inhibition during meditation (or slow breathing). Although the overlapping issue of the ZLE still remains, the ZLE was more robust than previous tachogram decomposition algorithms (Gauss, ARMAx and OSP) when RR dynamically fluctuates. Since the proposed approach requires only a single-lead ECG, we expect that it will be used in various fields, such as the internet of Medical Things (IoMT), digital healthcare, digital meditation, and digital therapeutics.»

Comments of the MRIS

If we look at the scientific report in Nature about a single lead ECG device which was used for meditation monitoring we can see that:

Respiratory sinus arrhythmia (RSA) induced by breathing is a dominant component of HRV, but its frequency depends on an individual’s breathing speed.
To address this RSA issue, the authors designed a novel HRV tachogram decomposition algorithm and new HRV indices.
In conclusion, the proposed method successfully assessed autonomic nervous system activity during meditation when respiration influences disrupted classical HRV.
The scientific report in Nature may be the first report on the identification of cardiac sympathetic inhibition during meditation or slow breathing.
The proposed approach requires only a single-lead ECG.
The authors expect that the method they published will be used in various fields, such as:

a) the internet of Medical Things (IoMT)
b) digital healthcare
c) digital meditation
d) and digital therapeutics

But applications which are based on this method published in this scientific report in Nature needs first to be developed and therefore this paper is currently not relevant for our application.

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