Last Updated on May 27, 2024 by pg@petergamma.org
Talha Iqbal
Postdoctoral Research Associate at University of Galway, Ireland
https://www.linkedin.com/in/talha-iqbal-550aa186/?originalSubdomain=ie
wrote recently a paper abou this:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9056464
Results
The Mean Absolute Error and the Root Mean Square Error of the proposed algorithm, with the optimal signal window size, are determined to be 2.05 breaths count per minute and 2.47 breaths count per minute, respectively, when tested on a publicly available dataset.
These results present a significant improvement in accuracy over previously reported methods. The proposed algorithm achieved comparable results to the existing algorithms in the literature on the BIDMC dataset (containing data of 53 subjects, each recorded for 8 min) for other signal window sizes.
Conclusion
The results endorse that integration of the proposed algorithm to a commercially available pulse oximetry device would expand its functionality from the measurement of oxygen saturation level and heart rate to the continuous measurement of the respiratory rate with good efficiency at home and in a clinical setting
comment of Peter Gamma from www.petergamma.org
- We currently now of no paper who use respiration rate estimation for physiology, we therefore suppose that it is too inaccurate for this purpose.
- Gold standard for HRM measurment are 3 channel ECG device, these are the most accurate one.
- But we do not know of any devices from for instance iWorx which use 3 channel ECG devices for respiration rate estimation.