Key result
A capnographic sensor based on the velocity of sound achieved classification accuracies of 91.3%, 87.76%, and 88.82% for healthy/COPD, healthy/CHF, and COPD/CHF cases, respectively.
Why the study?
Exhaled carbon dioxide concentration provides noninvasive, continuous information on metabolic and respiratory function, motivating a capnographic sensor based on sound velocity to diagnose cardiopulmonary disorders.
Does a capnographic sensor using an acoustic virial equation accurately measure exhaled CO2 and diagnose cardiopulmonary disorders compared to a standard sensor?
Does a capnographic sensor using an acoustic virial equation accurately measure exhaled CO2 and diagnose cardiopulmonary disorders compared to a standard sensor?
Effect estimate: squared correlation coefficient of 0.8732
A novel acoustic capnographic sensor demonstrates high correlation with standard sensors and good accuracy in classifying healthy individuals, COPD, and CHF patients.
The concentration of carbon dioxide (CO 2 ) in exhaled breath can provide both noninvasive and continuous information on the metabolic and respiratory functioning of an individual. A capnographic sensor based on the velocity of sound has been proposed to measure the concentration of carbon dioxide in exhaled air using an acoustic virial equation. The extracted capnographic signal is further utilized to diagnose cardiopulmonary disorders such as chronic obstructive pulmonary disease (COPD) and congestive heart failure (CHF). The capnographic signal obtained using the proposed sensor shows a good correlation with the signal from a standard sensor with a squared correlation coefficient of 0.8732. We achieved an accuracy of 91.3, 87.76, and 88.82% for healthy/COPD, healthy/CHF, and COPD/CHF classification cases, respectively. The performance indicates the suitability of the proposed method to be used as a diagnostic device for cardiorespiratory diseases.
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Bhagya et al. (2020) studied Chronic obstructive pulmonary disease (COPD) and congestive heart failure (CHF). Capnographic sensor based on the velocity of sound using an acoustic virial equation vs. Standard sensor was evaluated on Classification accuracy for healthy/COPD, healthy/CHF, and COPD/CHF cases (squared correlation coefficient of 0.8732). A capnographic sensor based on the velocity of sound achieved classification accuracies of 91.3%, 87.76%, and 88.82% for healthy/COPD, healthy/CHF, and COPD/CHF cases, respectively.
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