Digitization and Analysis of Capnography Using Image Processing Technique

Abstract

The study of carbon dioxide expiration is called capnometry. The graphical representation of capnometry is called capnography. There is a growing interest in the usage of capnography as the usage has expanded toward the study of metabolism, circulation, lung perfusion and diffusion, quality of spontaneous respiration, and patency of airways outside of its typical usage in the anesthetic and emergency medicine field. The parameters of the capnograph could be classified as carbon dioxide (CO₂) concentration and time points and coordinates, slopes angle, volumetric studies, and functional transformation of wave data. Up to date, there is no gold standard device for the calculation of the capnographic parameters. Capnography digitization using the image processing technique could serve as an option. From the algorithm we developed, eight identical breath waves were tested by four investigators. The values of the parameters chosen showed no significant difference between investigators. Although there were no significant differences between any of the parameters tested, there were a few related parameters that were not calculable. Further testing after refinement of the algorithm could be done. As more capnographic parameters are being derived and rediscovered by clinicians and researchers alike for both lung and non-lung-related diseases, there is a dire need for data analysis and interpretation. Although the proposed algorithm still needs minor refinements and further large-scale testing, we proposed that the digitization of the capnograph via image processing technique could serve as an intellectual option as it is fast, convenient, easy to use, and efficient.

Keywords: EtCO2; capnography; capnometry; end tidal carbon dioxide; time based capnography.

Figure 1

Capnographic image digitization algorithm.

Figure 2

Image processing algorithm of an image with capnograph. (A) Raw capnographic signal. (B) x-axis cropping. (C) y-axis cropping. (D) Breath waveform cropping. (E) Cropped breath waveform. (F) Binarized crop yield from image (E). (G) Duration optimized single breath waveform. (H) Skeletonized version of image (G). (I) “Digitized” signal.

Figure 3

(A) Raw capnographic signal. (B) “Digitized” signal with derived capnometric parameters. The black star and diamond are MATLAB derived plot coordinates for EtCO2 and Bohr's PACO2 respectively.