How can we estimate the respiration rate in Python for breath meditation with a higher accuracy than we have from a Garmin Fenix 6?

Last Updated on April 2, 2024 by pg@petergamma.org

Peter Gamma from www.petergamma.org currently uses a Garmin Fenix 6 for breath meditation:

Which is not very satistying for him personally as a physiologist.

We have alternative:ly the

Estimation of Respiratory Rate from ECG signal in Python programming language

from the

Faculty of Computer Science and Engineering: Conference papers

Eduard Žňava et. al. Slovak University of Technology in Bratislava, Faculty of Informatics and Information Technologies, Slovakia

https://repository.ukim.mk/bitstream/20.500.12188/25003/1/estimation-of-respiratory-rate-from-ecg-signal-in-python-programming-language.pdf

And the code for it can be found here:

Where can we find the Respiratory Rate Estimation Toolbox in Python?

then we have Nature reports about:

Single-lead ECG based autonomic nervous system assessment for meditation monitoring

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

as well as:

Open-source software for respiratory rate estimation using single-lead electrocardiograms

https://www.nature.com/articles/s41598-023-50470-0

But the goal of Peter Gamma from www.petergamma.org is not to write further nature reports, but to get a robust and affordable medical and research grade device to measure respiration rate during breath meditation:

3 channel ECG devices are gold standard for heart rate measurements – why not to test similarly with 3 respiration channels if we can build a robust & affordable device for gold standard for respiration rate measurement?

And a respiration rate estimation in Python which is more accurate than a Garmin Fenix 6 is a first step on this path. There is a big diversity of devices to measure respiration rate, and what we write here is a step forward in the development of a device which is suitable for breath meditation at the level of a scientfic or clinical study. And to see if the device is accurate enough for our application, is this not done best empirically by building and testing these devices? And if they seem to be accurate enough, they eventually can be validated in a scientific study. And we invite everybody to participate in the development of this new and promising device to measure respiration rate during breath meditation with an accuracy which is as high as possible, but still with a device which is robust and affordable.