Easiest way to get clinical & research grade respiration rate? – PETER GAMMA (Director & Physiologist), MEDITATION RESEARCH INSTITUTE SWITZERLAND (MRIS)

Last Updated on May 26, 2024 by pg@petergamma.org

This is according to our own little experience Peter H. Charlton’s Matlab respiratory rate estimation toolbox
The Matlab licence is about 1 000 USD.
Matlab furthermore requires an x86 processor and does not run for instance on Raspberry Pi’s which are arm based.
Octave which is a Matlab alternative does not require x86 processors and should also run on arm based SBCs.
But we suppose the toolbox runs also in Octave which is free.
EEGLAB which is much more complex runs in Octave as well.
We suggest for it to use a Raspberry Pi with OpenBCI and BrainFlow:

we suppose that there is code in LSL which only runs on x86 processors.
Peter H. Charltons respiratory rate estimation can also be used for clinical applications.
But we do not know of users who use it for this purpose.
A 3 channel ECG device which would be necessary to use it to monitor vital signs is a rather fragile device.
Spirometers for clinical applications are very expensive.
But for accurate clinical grate respiration rate Peter H. Charlton’s Matlab Respiratorey Rate estimation toolbox is a good starting point
It can for instance be built from OpenBCI
But as far as we know nobody has ever shown that the setup which is discussed here work built from:
Matlab Respiratory Rate Estimation Toolbox
Octave
OpenBCI
BrainFlow
Raspberry Pi
If you want to write a paper about it, go for it.
There might also be legal issues if we use the Matlab Respiratory Rate estimation toolbox without Matlab licence.
There it is better to get the code elsewere.
But ususally for clinical and research grade applications expensive spirometer devices are used, which are more robust than respiratory rate estimation devices.
We would prefer Python over the Matlab respiratory rate estimation toolbox.

There is a Nature scientific report about Python open-source software for respiratory rate estimation:

Nature scientific report about Python open-source software for respiratory rate estimation using single-lead electrocardiograms

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