Non-contact Respiratory Rate Monitoring Based on the Principal Component Analysis

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.

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