Abstract: Assessing respiratory rate is a critical determinant of one’s health status. The proposed approach relies on principal component analysis (PCA) for the continuous monitoring of breathing rate using an RGB camera. This method employs re-mote plethysmography, a video-based technique enabling contact-less tracking of blood volume fluctuations by detecting variations in pixel intensity on the skin. These pixels encompass the red, blue, and green channels, whose values, post-PCA dimensionality reduction, encode the signal containing vital information about the breathing rate. To assess the method’s performance, it was tested on a group of seven volunteers, including individuals of both genders. The results reveal a Mean Absolute Deviation of 0.714 BPM and a Root Mean Square Error of 2.035 BPM when comparing the experimental measurements to the actual readings.

Hoda El Boussaki, Rachid Latif, Amine Saddik, Zakaria El Khadiri and Hicham El Boujaoui, “Non-contact Respiratory Rate Monitoring Based on the Principal Component Analysis” International Journal of Advanced Computer Science and Applications(IJACSA), 14(9), 2023. http://dx.doi.org/10.14569/IJACSA.2023.01409106

@article{Boussaki2023,
title = {Non-contact Respiratory Rate Monitoring Based on the Principal Component Analysis},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.01409106},
url = {http://dx.doi.org/10.14569/IJACSA.2023.01409106},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {9},
author = {Hoda El Boussaki and Rachid Latif and Amine Saddik and Zakaria El Khadiri and Hicham El Boujaoui}
}